2023/12/26 更新

写真a

タケムラ ノリコ
武村 紀子
TAKEMURA Noriko
Scopus 論文情報  
総論文数: 0  総Citation: 0  h-index: 9

Citation Countは当該年に発表した論文の被引用数

メールアドレス
メールアドレス
研究室住所
福岡県飯塚市川津680-4
研究室電話
0948-29-7917
外部リンク

研究キーワード

  • 行動センシング,人の状態認識,知的支援システム

研究分野

  • 情報通信 / 知覚情報処理

  • 情報通信 / ヒューマンインタフェース、インタラクション

出身学校

  • 2006年03月   大阪大学   工学部   応用理工学科   卒業   日本国

出身大学院

  • 2010年09月   大阪大学   工学研究科   知能・機能創成工学専攻   博士課程・博士後期課程   修了   日本国

  • 2007年09月   大阪大学   工学研究科   機械工学専攻   修士課程・博士前期課程   修了   日本国

取得学位

  • 大阪大学  -  博士(工学)   2010年09月

  • 大阪大学  -  修士(工学)   2007年09月

学外略歴

  • 2017年10月 - 2022年03月   大阪大学   データビリティフロンティア機構   准教授   日本国

  • 2016年02月 - 2017年09月   大阪大学   産業科学研究所   特任助教   日本国

  • 2014年04月 - 2016年01月   大阪大学   大学院基礎工学研究科   助教   日本国

  • 2010年11月 - 2014年03月   大阪大学   大学院基礎工学研究科   研究員   日本国

所属学会・委員会

  •   日本ロボット学会   日本国

  •   計測自動制御学会   日本国

  •   日本バーチャルリアリティ学会   日本国

論文

  • Uncertainty-Aware Gait-Based Age Estimation and its Applications 査読有り 国際誌

    Xu C., Sakata A., Makihara Y., Takemura N., Muramatsu D., Yagi Y., Lu J.

    IEEE Transactions on Biometrics, Behavior, and Identity Science   3 ( 4 )   479 - 494   2021年10月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Gait-based age estimation is a key technique for many applications. It is well known that age estimation uncertainty is highly dependent on age (i.e., small for children and large for adults), and it is important to know the uncertainty for the above-mentioned applications. Therefore, we propose a method for uncertainty-aware gait-based age estimation by introducing a label distribution learning framework. Specifically, we design a network that takes an appearance-based gait feature as input and outputs discrete label distributions in the integer age domain. We then train the network to minimize a loss function, which is defined as the dissimilarity between the estimated age distribution and the ground-truth age distribution, in addition to the conventional mean absolute error for the estimated age. Additionally, we demonstrate that uncertainty-aware gait-based age estimation is beneficial for two applications: person search by age query and people counting by age group. Experiments on the world's largest gait database, OULP-Age, demonstrated that the proposed method can successfully represent age estimation uncertainty, and outperforms or is comparable with state-of-the-art methods in terms of age estimation accuracy. Moreover, we demonstrated the effectiveness of the uncertainty-aware framework in applications to person search and people counting through experiments on the database.

    DOI: 10.1109/TBIOM.2021.3080300

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85111106805&origin=inward

  • Physical Fatigue Detection from Gait Cycles via a Multi-Task Recurrent Neural Network 査読有り 国際誌

    Aoki K., Nishikawa H., Makihara Y., Muramatsu D., Takemura N., Yagi Y.

    IEEE Access   9   127565 - 127575   2021年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    This paper describes a deep learning approach to classify physically fatigued and non-fatigued gait cycles via a recurrent neural network (RNN), where each gait cycle is represented as a time series of three-dimensional coordinates of body joints. Gait cycles inherently have large intra-class variations caused by gait stance differences (e.g., which foot is supporting/swinging) at the beginning of each gait cycle, which makes it difficult to identify subtle differences induced by fatigue. To overcome these difficulties, we introduce a supporting foot-aware RNN model in a multi-task learning framework for better fatigue detection. More specifically, the RNN model has two branches of layers: one is assigned to the main task of fatigue classification and the other is assigned to the auxiliary task of estimating the first supporting foot in the gait cycles. We collected physically fatigued and non-fatigued gait cycles from eight subjects and conducted experiments to evaluate the accuracies of the proposed multi-task model in comparison to a single-task model. As a result, the proposed method achieved an overall area under curve (AUC) of 0.860 for fatigue classification in a leave-one-subject-out cross-validation, and an AUC of 0.915 in a leave-one-day-out evaluation. It can be concluded from the experimental results that a fatigue detection system for daily use, especially for screening purposes, is very feasible on the basis of the proposed approach.

    DOI: 10.1109/ACCESS.2021.3110841

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85114741453&origin=inward

  • LEARNERS’ EFFICIENCY PREDICTION USING FACIAL BEHAVIOR ANALYSIS 査読有り 国際誌

    Verma M., Nakashima Y., Kobori H., Takaoka R., Takemura N., Kimura T., Nagahara H., Numao M., Shinohara K.

    Proceedings - International Conference on Image Processing, ICIP   2021-September   1084 - 1088   2021年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In the e-learning context, how much the learner is concentrated and engaged, or the learners’ efficiency, is essential for providing adaptive and flexible materials, timely suggestions, etc., which can lead to efficient learning. In this work, we explore to predict learners’ efficiency with a realistic configuration, in which we use a webcam or a laptop PC’s built-in camera. Specifically, we first provide a feasible definition of the learners’ efficiency, and based on this definition, we predict one’s efficiency from facial behavior. We predict the learners’ efficiency using various convolutional neural networks. Results are discussed using different evaluation metrics.

    DOI: 10.1109/ICIP42928.2021.9506203

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85125599760&origin=inward

  • Detecting Drowsy Learners at the Wheel of e-Learning Platforms with Multimodal Learning Analytics 査読有り 国際誌

    Kawamura R., Shirai S., Takemura N., Alizadeh M., Cukurova M., Takemura H., Nagahara H.

    IEEE Access   9   115165 - 115174   2021年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Learners are expected to stay wakeful and focused while interacting with e-learning platforms. Although wakefulness of learners strongly relates to educational outcomes, detecting drowsy learning behaviors only from log data is not an easy task. In this study, we describe the results of our research to model learners' wakefulness based on multimodal data generated from heart rate, seat pressure, and face recognition. We collected multimodal data from learners in a blended course of informatics and conducted two types of analysis on them. First, we clustered features based on learners' wakefulness labels as generated by human raters and ran a statistical analysis. This analysis helped us generate insights from multimodal data that can be used to inform learner and teacher feedback in multimodal learning analytics. Second, we trained machine learning models with multiclass-Support Vector Machine (SVM), Random Forest (RF) and CatBoost Classifier (CatBoost) algorithms to recognize learners' wakefulness states automatically. We achieved an average macro-F1 score of 0.82 in automated user-dependent models with CatBoost. We also showed that compared to unimodal data from each sensor, the multimodal sensor data can improve the accuracy of models predicting the wakefulness states of learners while they are interacting with e-learning platforms.

    DOI: 10.1109/ACCESS.2021.3104805

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85113264115&origin=inward

  • How confident are you in your estimate of a human age? uncertainty-aware gait-based age estimation by label distribution learning 査読有り 国際誌

    Sakata A., Makihara Y., Takemura N., Muramatsu D., Yagi Y.

    IJCB 2020 - IEEE/IAPR International Joint Conference on Biometrics   2020年09月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Gait-based age estimation is one of key techniques for many applications (e.g., finding lost children/aged wanders). It is well known that the age estimation uncertainty is highly dependent on ages (i.e., it is generally small for children while is large for adults/the elderly), and it is important to know the uncertainty for the above-mentioned applications. We therefore propose a method of uncertainty-aware gait-based age estimation by introducing a label distribution learning framework. More specifically, we design a network which takes an appearance-based gait feature as an input and outputs discrete label distributions in the integer age domain. Experiments with the world-largest gait database OULP-Age show that the proposed method can successfully represent the uncertainty of age estimation and also outperforms or is comparable to the state-of-the-art methods.

    DOI: 10.1109/IJCB48548.2020.9304914

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85099694395&origin=inward

  • Estimation of wakefulness in video-based lectures based on multimodal data fusion 査読有り 国際誌

    Kawamura R., Shirai S., Aizadeh M., Takemura N., Nagahara H.

    UbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers   50 - 53   2020年09月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In distance learning contexts, drowsiness is a major factor which disturbs learning. However, it is not easy for instructors to monitor students' wakefulness. In order to improve learning efficacy, accurate estimation of wakefulness is needed. In this study, we propose a multimodal wakefulness estimation method based on face and body movement information. We utilize web-cameras to obtain facial and head (face-head) movements and pressure mats for body movements, the latter of which can record the distribution of upper body pressure while watching video lectures. To confirm the effectiveness of multimodal data for wakefulness estimation, we conducted an experiment to collect data from students as they engaged in e-learning and their level of wakefulness was annotated in one-second windows. We extracted 45 features from face-head movements, and 80 features from seat pressure data. Two types of fusion methods, early and decision level fusion were applied, and the late fusion approach achieved an average F1-macro score of 0.70 in three levels of wakefulness estimation, which is higher than the unimodal approach. This result indicates that fusion of facial images and seat pressure features can be effective for learner wakefulness estimation.

    DOI: 10.1145/3410530.3414386

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091871487&origin=inward

  • Gait-based age estimation using multi-stage convolutional neural network 査読有り 国際誌

    Sakata A., Takemura N., Yagi Y.

    IPSJ Transactions on Computer Vision and Applications   11 ( 1 )   2019年12月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    Gait-based age estimation has been extensively studied for various applications because of its high practicality. In this paper, we propose a gait-based age estimation method using convolutional neural networks (CNNs). Because gait features vary depending on a subject’s attributes, i.e., gender and generation, we propose the following three CNN stages: (1) a CNN for gender estimation, (2) a CNN for age-group estimation, and (3) a CNN for age regression. We conducted experiments using a large population gait database and confirm that the proposed method outperforms state-of-the-art benchmarks.

    DOI: 10.1186/s41074-019-0054-2

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85067196767&origin=inward

  • Spatio-temporal silhouette sequence reconstruction for gait recognition against occlusion 査読有り 国際誌

    Uddin M.Z., Muramatsu D., Takemura N., Ahad M.A.R., Yagi Y.

    IPSJ Transactions on Computer Vision and Applications   11 ( 1 )   2019年12月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Gait-based features provide the potential for a subject to be recognized even from a low-resolution image sequence, and they can be captured at a distance without the subject’s cooperation. Person recognition using gait-based features (gait recognition) is a promising real-life application. However, several body parts of the subjects are often occluded because of beams, pillars, cars and trees, or another walking person. Therefore, gait-based features are not applicable to approaches that require an unoccluded gait image sequence. Occlusion handling is a challenging but important issue for gait recognition. In this paper, we propose silhouette sequence reconstruction from an occluded sequence (sVideo) based on a conditional deep generative adversarial network (GAN). From the reconstructed sequence, we estimate the gait cycle and extract the gait features from a one gait cycle image sequence. To regularize the training of the proposed generative network, we use adversarial loss based on triplet hinge loss incorporating Wasserstein GAN (WGAN-hinge). To the best of our knowledge, WGAN-hinge is the first adversarial loss that supervises the generator network during training by incorporating pairwise similarity ranking information. The proposed approach was evaluated on multiple challenging occlusion patterns. The experimental results demonstrate that the proposed approach outperforms the existing state-of-the-art benchmarks.

    DOI: 10.1186/s41074-019-0061-3

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85075430465&origin=inward

  • Facial Expression Recognition with Skip-Connection to Leverage Low-Level Features 査読有り 国際誌

    Verma M., Kobori H., Nakashima Y., Takemura N., Nagahara H.

    Proceedings - International Conference on Image Processing, ICIP   2019-September   51 - 55   2019年09月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Deep convolutional neural networks (CNNs) have established their feet in the ground of computer vision and machine learning, used in various applications. In this work, an attempt is made to learn a CNN for a task of facial expression recognition (FER). Our network has convolutional layers linked with an FC layer with a skip-connection to the classification layer. Motivation behind this design is that lower layers of a CNN are responsible for lower level features, and facial expressions can be mainly encoded in low-to-mid level features. Hence, in order to leverage the responses from lower layers, all convo-lutional layers are integrated via FC layers. Moreover, a network with shared parameters is used to extract landmark motion trajectory features. These visual and landmark features are fused to improve the performance. Our method is evaluated on the CK+ and Oulu-CASIA facial expression datasets.

    DOI: 10.1109/ICIP.2019.8803396

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076807232&origin=inward

  • On Input/Output Architectures for Convolutional Neural Network-Based Cross-View Gait Recognition 査読有り 国際誌

    Takemura N., Makihara Y., Muramatsu D., Echigo T., Yagi Y.

    IEEE Transactions on Circuits and Systems for Video Technology   29 ( 9 )   2708 - 2719   2019年09月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    In this paper, we discuss input/output architectures for convolutional neural network (CNN)-based cross-view gait recognition. For this purpose, we consider two aspects: verification versus identification and the tradeoff between spatial displacements caused by subject difference and view difference. More specifically, we use the Siamese network with a pair of inputs and contrastive loss for verification and a triplet network with a triplet of inputs and triplet ranking loss for identification. The aforementioned CNN architectures are insensitive to spatial displacement, because the difference between a matching pair is calculated at the last layer after passing through the convolution and max pooling layers; hence, they are expected to work relatively well under large view differences. By contrast, because it is better to use the spatial displacement to its best advantage because of the subject difference under small view differences, we also use CNN architectures where the difference between a matching pair is calculated at the input level to make them more sensitive to spatial displacement. We conducted experiments for cross-view gait recognition and confirmed that the proposed architectures outperformed the state-of-the-art benchmarks in accordance with their suitable situations of verification/identification tasks and view differences.

    DOI: 10.1109/TCSVT.2017.2760835

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85031904248&origin=inward

  • Multi-view large population gait dataset and its performance evaluation for cross-view gait recognition 査読有り 国際誌

    Takemura N., Makihara Y., Muramatsu D., Echigo T., Yagi Y.

    IPSJ Transactions on Computer Vision and Applications   10 ( 1 )   2018年12月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    This paper describes the world’s largest gait database with wide view variation, the “OU-ISIR gait database, multi-view large population dataset (OU-MVLP)”, and its application to a statistically reliable performance evaluation of vision-based cross-view gait recognition. Specifically, we construct a gait dataset that includes 10,307 subjects (5114 males and 5193 females) from 14 view angles ranging 0° −90°, 180° −270°. In addition, we evaluate various approaches to gait recognition which are robust against view angles. By using our dataset, we can fully exploit a state-of-the-art method requiring a large number of training samples, e.g., CNN-based cross-view gait recognition method, and we validate effectiveness of such a family of the methods.

    DOI: 10.1186/s41074-018-0039-6

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85042469165&origin=inward

  • The OU-ISIR Large Population Gait Database with real-life carried object and its performance evaluation 査読有り 国際誌

    Uddin M.Z., Ngo T.T., Makihara Y., Takemura N., Li X., Muramatsu D., Yagi Y.

    IPSJ Transactions on Computer Vision and Applications   10 ( 1 )   2018年12月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    In this paper, we describe the world’s largest gait database with real-life carried objects (COs), which has been made publicly available for research purposes, and its application to the performance evaluation of vision-based gait recognition. Whereas existing databases for gait recognition include at most 4007 subjects, we constructed an extremely large-scale gait database that includes 62,528 subjects, with an equal distribution of males and females, and ages ranging from 2 to 95 years old. Moreover, whereas existing gait databases consider a few predefined CO positions on a subject’s body, we constructed a database that contained unconstrained variations of COs being carried in unconstrained positions. Additionally, gait samples were manually classified into seven carrying status (CS) labels. The extremely large-scale gait database enabled us to evaluate recognition performance under cooperative and uncooperative settings, the impact of the training data size, the recognition difficulty level of the CS labels, and the possibility of the classification of CS labels. Particularly, the latter two performance evaluations have not been investigated in previous gait recognition studies.

    DOI: 10.1186/s41074-018-0041-z

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85047815580&origin=inward

  • Mental fatigue estimation based on luminance changes in facial images 査読有り 国際誌

    Kawamura R., Takemura N., Sato K.

    SII 2016 - 2016 IEEE/SICE International Symposium on System Integration   526 - 531   2017年02月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In this study, we propose a method for estimating a user's fatigue resulting from mental load, such as office work, based on changes of luminance in facial images. Because these changes are influenced by vital signs such as heart rate and blood pressure, we consider that the level of fatigue is predictable with high accuracy by combining the features in the changes of luminance in the facial area. We thus detected 13 facial parts and estimated subjects' fatigue using feature values based on luminance changes in each facial part. The experimental results revealed that fatigue states could be estimated with an accuracy of 92%.

    DOI: 10.1109/SII.2016.7844052

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015433021&origin=inward

  • 照明の微小変動に誘発される無意識的行動に基づく快不快推定 査読有り

    菊川 剛, 武村 紀子, 佐藤 宏介

    システム制御情報学会論文誌 ( 一般社団法人 システム制御情報学会 )   30 ( 5 )   183 - 190   2017年01月

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    担当区分:責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

    <p>We propose a method for estimating the user's comfort/discomfort in response to the lighting condition during desk work. We fluctuate the lighting condition slightly, and the user's comfort/discomfort is estimated according to unconscious behaviors induced by the illuminance fluctuation. The experimental results show that the proposed method with illuminance fluctuation outperforms the conventional method with constant illuminance.</p>

    DOI: 10.5687/iscie.30.183

    CiNii Article

    CiNii Research

    その他リンク: https://www.jstage.jst.go.jp/article/iscie/30/5/30_183/_pdf

  • 発話時の表情変化に基づいた精神疲労の推定 査読有り

    川村 亮介, 武村 紀子, 佐藤 宏介

    計測自動制御学会論文集 ( 公益社団法人 計測自動制御学会 )   53 ( 1 )   90 - 98   2017年01月

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    担当区分:責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

    In this study, we propose the method for estimating the user's fatigue due to mental load like a desk work based on information of facial expressions. It is, however, difficult to estimate the mental fatigue using ambient sensors information because of a small change of user's appearance. Thus the user's mental fatigue is measured based on his/her facial expression during speech. As experimental results, recognition rate base on facial expression during speech marks higher rate (at most 89%) than that based on facial expression without speech. In addition, we conduct the another experiment for different types of workload, it is confirmed that proposed method is effective for various fatigue.

    DOI: 10.9746/sicetr.53.90

    CiNii Article

    CiNii Research

    その他リンク: https://www.jstage.jst.go.jp/article/sicetr/53/1/53_90/_pdf

  • Mental fatigue estimation based on facial expressions during speech 査読有り 国際誌

    Kawamura R., Takemura N., Sato K.

    2015 IEEE/SICE International Symposium on System Integration, SII 2015   223 - 228   2016年02月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In this study, we propose a method to estimate a user's fatigue state resulting from mental load (e.g., from office work) based on facial expression information. Changes in appearance because of mental fatigue are subtle and difficult to estimate using ambient sensor information. Thus, we estimate the user's mental fatigue based on facial expressions during speech. The experimental results show that the fatigue state can be recognized with up to an 89% accuracy. Furthermore, we confirm that our method enables highly accurate estimation of the fatigue state without dependence on the task types.

    DOI: 10.1109/SII.2015.7404982

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84963737523&origin=inward

  • Multi-sensor-based Ambient Sensing System for the Estimation of Comfort/Discomfort to Lighting Condition During Desk Work 査読有り 国際誌

    Yoshimizu Kengo, Takemura Noriko, Iwai Yoshio, Sato Kosuke

    Journal of Information Processing ( 一般社団法人 情報処理学会 )   23 ( 6 )   776 - 783   2015年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    A multi-sensor-based ambient sensing system is proposed for estimating the user's comfort/discomfort in response to the lighting condition during desk work. The user's comfort/discomfort is estimated according to facial expression, body sway, writing motion and frequency of drinking measured by sensors embedded in the environment. The recognition rate of the user's comfort/discomfort under the lighting condition that induces different feelings of comfort depending on the user's state of the day is evaluated in an experimental environment. As a result, the recognition rate of the user's comfort/discomfort on a two-point scale is 91% when selecting a suitable combination of ambient sensors. Furthermore, it is suggested that not only information of facial expression but also the information of body sway, writing motion and frequency of drinking is useful for the estimation of comfort/discomfort.

    DOI: 10.2197/ipsjjip.23.776

    Scopus

    CiNii Article

    CiNii Research

    その他リンク: http://id.nii.ac.jp/1001/00146086/

  • Multi-sensor-based ambient sensing system for the estimation of comfort/discomfort during desk work 査読有り 国際誌

    Yoshimizu K., Takemura N., Iwai Y., Sato K.

    2014 IEEE/SICE International Symposium on System Integration, SII 2014   425 - 430   2014年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    A multi-sensor-based ambient sensing system is proposed for estimating the user's comfort/discomfort in response to the lighting condition during desk work. The user's comfort/discomfort is estimated according to facial expression, body sway, writing motion and frequency of drinking measured by sensors embedded in the environment. The purpose of the system is to make a robust estimation even under a lighting condition that induces different feelings of comfort depending on the person. To this end, optimal sensor information is selected adaptively depending on the lighting condition among sensor information measured by multiple sensors. It is experimentally confirmed that the user's comfort/discomfort can be estimated even in such mild lighting conditions. The recognition rate of user's comfort on a seven-point scale is 72% when using only ambient sensors (i.e., the subject does not wear sensors).

    DOI: 10.1109/SII.2014.7028076

    Scopus

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  • Person segmentation and identification across multiple wearable cameras 査読有り 国際誌

    Noriko Takemura, Haruya Sakashita, Shizuka Shirai, Mehrasa Alizadeh, Hajime Nagahara

    Proc. SPIE 12749, Sixteenth International Conference on Quality Control by Artificial Vision   2023年07月

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    担当区分:筆頭著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    DOI: 10.1117/12.2692433

  • 脳波による脳機能ネットワークの結合性を用いた RNNによる不安状態判別評価 査読有り

    山本 祐輔, 原地 絢斗, 村松 歩, 長原 一, 武村 紀子, 水野(松本) 由子, 下條 真司

    電気学会論文誌C   2023年04月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • Subjective Difficulty Estimation of Educational Comics Using Gaze Features 査読有り 国際誌

    Kenya Sakamoto, Shizuka Shirai, Noriko Takemura, Jason Orlosky, Hiroyuki Nagataki, Mayumi Ueda, Yuki Uranishi, Haruo Takemura

    IEICE Transactions on Information and Systems   2023年02月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

  • Development of a vertex finding algorithm using Recurrent Neural Network 査読有り 国際誌

    Goto K., Suehara T., Yoshioka T., Kurata M., Nagahara H., Nakashima Y., Takemura N., Iwasaki M.

    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment   1047   2023年02月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Deep learning is a rapidly-evolving technology with the possibility to significantly improve the physics reach of collider experiments. In this study we developed a novel vertex finding algorithm for future lepton colliders such as the International Linear Collider. We deploy two networks: one consists of simple fully-connected layers to look for vertex seeds from track pairs, and the other is a customized Recurrent Neural Network with an attention mechanism and an encoder–decoder structure to associate tracks to the vertex seeds. The performance of the vertex finder is compared with the standard ILC vertex reconstruction algorithm.

    DOI: 10.1016/j.nima.2022.167836

    Scopus

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  • Subjective Difficulty Estimation of Educational Comics Using Gaze Features 査読有り

    Sakamoto K., Shirai S., Takemura N., Orlosky J., Nagataki H., Ueda M., Uranishi Y., Takemura H.

    IEICE Transactions on Information and Systems   E106.D ( 5 )   1038 - 1048   2023年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    This study explores significant eye-gaze features that can be used to estimate subjective difficulty while reading educational comics. Educational comics have grown rapidly as a promising way to teach difficult topics using illustrations and texts. However, comics include a variety of information on one page, so automatically detecting learners' states such as subjective difficulty is difficult with approaches such as system logbased detection, which is common in the Learning Analytics field. In order to solve this problem, this study focused on 28 eye-gaze features, including the proposal of three new features called "Variance in Gaze Convergence,""Movement between Panels,"and "Movement between Tiles"to estimate two degrees of subjective difficulty. We then ran an experiment in a simulated environment using Virtual Reality (VR) to accurately collect gaze information. We extracted features in two unit levels, page- and panelunits, and evaluated the accuracy with each pattern in user-dependent and user-independent settings, respectively. Our proposed features achieved an average F1 classification-score of 0.721 and 0.742 in user-dependent and user-independent models at panel unit levels, respectively, trained by a Support Vector Machine (SVM).

    DOI: 10.1587/transinf.2022EDP7100

    Scopus

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  • Evaluation of Anxiety State Discrimination by Recurrent Neural Network using the Connectivity of Brain Function Network by EEG 査読有り

    Yamamoto Y., Harachi K., Muramatsu A., Nagahara H., Takemura N., Mizuno-Matsumoto Y., Shimojo S.

    IEEJ Transactions on Electronics, Information and Systems   143 ( 4 )   430 - 440   2023年01月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)

    This study examined the differences in functional brain network over time between different anxiety states and evaluated their usefulness in neural networks (NN). Seventeen young adults with high-anxiety and 13 young adults with low-anxiety were examined. The subjects were given three stimulations: resting, pleasant, and unpleasant stimuli, and Electroencephalogram (EEG) was measured immediately after the stimuli. EEG was analyzed for the alpha band using coherence analysis and graph theory. We evaluated the classification accuracy of anxiety states by NN and recurrent neural networks (RNN). The results showed the information processing process and structure of the brain functional network to emotional stimuli differed over time depending on the anxiety state. The time series data of coherence and graph theoretical indicator by EEG would be considered to be useful for discriminating anxiety states using RNN.

    DOI: 10.1541/ieejeiss.143.430

    Scopus

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  • Criteria for detection of possible risk factors for mental health problems in undergraduate university students 査読有り 国際誌

    Ishimaru D., Adachi H., Mizumoto T., Erdelyi V., Nagahara H., Shirai S., Takemura H., Takemura N., Alizadeh M., Higashino T., Yagi Y., Ikeda M.

    Frontiers in Psychiatry   14   2023年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Introduction: Developing approaches for early detection of possible risk clusters for mental health problems among undergraduate university students is warranted to reduce the duration of untreated illness (DUI). However, little is known about indicators of need for care by others. Herein, we aimed to clarify the specific value of study engagement and lifestyle habit variables in predicting potentially high-risk cluster of mental health problems among undergraduate university students. Methods: This cross-sectional study used a web-based demographic questionnaire [the Utrecht Work Engagement Scale for Students (UWES-S-J)] as study engagement scale. Moreover, information regarding life habits such as sleep duration and meal frequency, along with mental health problems such as depression and fatigue were also collected. Students with both mental health problems were classified as high risk. Characteristics of students in the two groups were compared. Univariate logistic regression was performed to identify predictors of membership. Receiver Operating Characteristic (ROC) curve was used to clarify the specific values that differentiated the groups in terms of significant predictors in univariate logistic analysis. Cut-off point was calculated using Youden index. Statistical significance was set at p < 0.05. Results: A total of 1,644 students were assessed, and 30.1% were classified as high-risk for mental health problems. Significant differences were found between the two groups in terms of sex, age, study engagement, weekday sleep duration, and meal frequency. In the ROC curve, students who had lower study engagement with UWES-S-J score < 37.5 points (sensitivity, 81.5%; specificity, 38.0%), <6 h sleep duration on weekdays (sensitivity, 82.0%; specificity, 24.0%), and < 2.5 times of meals per day (sensitivity, 73.3%; specificity, 35.8%), were more likely to be classified into the high-risk group for mental health problems. Conclusion: Academic staff should detect students who meet these criteria at the earliest and provide mental health support to reduce DUI among undergraduate university students.

    DOI: 10.3389/fpsyt.2023.1184156

    Scopus

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  • 撮影角度抑制学習を用いた歩容に基づく年齢推定 査読有り

    山野広大,村松大吾,武村紀子,八木康史

    電子情報通信学会論文誌 A   2022年12月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • Corpus Construction for Historical Newspapers: A Case Study on Public Meeting Corpus Construction Using OCR Error Correction 査読有り 国際誌

    Tanaka K., Chu C., Kajiwara T., Nakashima Y., Takemura N., Nagahara H., Fujikawa T.

    SN Computer Science   3 ( 6 )   2022年11月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Large text corpora are indispensable for natural language processing. However, in various fields such as literature and humanities, many documents to be studied are only scanned to images, but not converted to text data. Optical character recognition (OCR) is a technology to convert scanned document images into text data. However, OCR often misrecognizes characters due to the low quality of the scanned document images, which is a crucial factor that degrades the quality of constructed text corpora. This paper works on corpus construction for historical newspapers. We present a corpus construction method based on a pipeline of image processing, OCR, and filtering. To improve the quality, we further propose to integrate OCR error correction. To this end, we manually construct an OCR error correction dataset in the historical newspaper domain, propose methods to improve a neural OCR correction model and compare various OCR error correction models. We evaluate our corpus construction method on the accuracy of extracting articles of a specific topic to construct a historical newspaper corpus. As a result, our method improves the article extraction F score by 1.7 % via OCR error correction comparing to previous work. This verifies the effectiveness of OCR error correction for corpus construction.

    DOI: 10.1007/s42979-022-01393-6

    Scopus

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  • 脳波と心電図を用いた周波数解析による定量化と不快情動判別評価 査読有り

    山本 祐輔, 田中 さや, 原地 絢斗, 村松 歩, 武村 紀子, 長原 一, 水野(松本) 由子, 下條 真司

    日本知能情報ファジィ学会誌   2022年08月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • Information Extraction from Public Meeting Articles 査読有り 国際誌

    Virgo F.G., Chu C., Ogawa T., Tanaka K., Ashihara K., Nakashima Y., Takemura N., Nagahara H., Fujikawa T.

    SN Computer Science   3 ( 4 )   2022年07月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Public meeting articles are the key to understanding the history of public opinion and public sphere in Australia. Information extraction from public meeting articles can obtain new insights into Australian history. In this paper, we create an information extraction dataset in the public meeting domain. We manually annotate the date and time, place, purpose, people who requested the meeting, people who convened the meeting, and people who were convened of 1258 public meeting articles. We further present an information extraction system, which formulates information extraction from public meeting articles as a machine reading comprehension task. Experiments indicate that our system can achieve an F1 score of 74.98% for information extraction from public meeting articles.

    DOI: 10.1007/s42979-022-01176-z

    Scopus

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  • Information Extraction from Public Meeting Articles 査読有り 国際誌

    Virgo Giovanni Felix, Chu Chenhui, Ogawa Takaya, Tanaka Koji, Ashihara Kazuki, Nakashima Yuta, Takemura Noriko, Nagahara Hajime, Fujikawa Takao

    SN Computer Science ( Springer Nature )   3   2022年05月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Public meeting articles are the key to understanding the history of public opinion and public sphere in Australia. Information extraction from public meeting articles can obtain new insights into Australian history. In this paper, we create an information extraction dataset in the public meeting domain. We manually annotate the date and time, place, purpose, people who requested the meeting, people who convened the meeting, and people who were convened of 1258 public meeting articles. We further present an information extraction system, which formulates information extraction from public meeting articles as a machine reading comprehension task. Experiments indicate that our system can achieve an F1 score of 74.98% for information extraction from public meeting articles.

    CiNii Research

  • Multi-label Disengagement and Behavior Prediction in Online Learning 査読有り 国際誌

    Verma M., Nakashima Y., Takemura N., Nagahara H.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   13355 LNCS   633 - 639   2022年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Student disengagement prediction in online learning environments is beneficial in various ways, especially to help provide timely cues to make some feedback or stimuli to the students. In this work, we propose a neural network-based model to predict students’ disengagement, as well as other behavioral cues, which might be relevant to students’ performance, using facial image sequences. For training and evaluating our model, we collected samples from multiple participants and annotated them with temporal segments of disengagement and other relevant behavioral cues with our multiple in-house annotators. We present prediction results of all behavior cues along with baseline comparison.

    DOI: 10.1007/978-3-031-11644-5_60

    Scopus

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  • Incorporation of Extra Pseudo Labels for CNN-based Gait Recognition 査読有り 国際誌

    Muramatsu D., Moriwaki K., Maruya Y., Takemura N., Yagi Y.

    BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group   2022年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    CNN is a major model used for image-based recognition tasks, including gait recognition, and many CNN-based network structures and/or learning frameworks have been proposed. Among them, we focus on approaches that use multiple labels for learning, typified by multi-task learning. These approaches are sometimes used to improve the accuracy of the main task by incorporating extra labels associated with sub-tasks. The incorporated labels for learning are usually selected from real tasks heuristically; for example, gender and/or age labels are incorporated together with subject identity labels. We take a different approach and consider a virtual task as a sub-task, and incorporate pseudo output labels together with labels associated with the main task and/or real task. In this paper, we focus on a gait-based person recognition task as the main task, and we discuss the effectiveness of virtual tasks with different pseudo labels for construction of a CNN-based gait feature extractor.

    DOI: 10.1109/BIOSIG55365.2022.9897053

    Scopus

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  • Comparison of Mental State Discrimination Accuracy by Pulse Wave Using Multi-Layer Perceptron and Recurrent Neural Network 査読有り

    Harachi K., Yamamoto Y., Muramatsu A., Nagahara H., Takemura N., Mizuno-Matsumoto Y., Shimojo S.

    IEEJ Transactions on Electronics, Information and Systems   140 ( 10 )   1115 - 1122   2022年01月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)

    This research aimed to compare of accuracy for machine learning using pulse wave. The subjects were 32 healthy young adults. They were divided to two groups by psychological tests. The pulse waves were measured during four emotional audiovisual stimuli. The subjects were discriminated into the mental stable or the mental unstable by Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN) by using pulse wave, and the accuracy was calculated. The rate of the RNN was higher than that of the MLP for the most of the stimuli. These results suggest that RNNs would suitable for machine learning using pulse wave.

    DOI: 10.1541/ieejeiss.142.1115

    Scopus

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  • A Japanese Dataset for Subjective and Objective Sentiment Polarity Classification in Micro Blog Domain 査読有り 国際誌

    Suzuki H., Miyauchi Y., Akiyama K., Kajiwara T., Ninomiya T., Takemura N., Nakashima Y., Nagahara H.

    2022 Language Resources and Evaluation Conference, LREC 2022   7022 - 7028   2022年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    We annotate 35,000 SNS posts with both the writer's subjective sentiment polarity labels and the reader's objective ones to construct a Japanese sentiment analysis dataset. Our dataset includes intensity labels (none, weak, medium, and strong) for each of the eight basic emotions by Plutchik (joy, sadness, anticipation, surprise, anger, fear, disgust, and trust) as well as sentiment polarity labels (strong positive, positive, neutral, negative, and strong negative). Previous studies on emotion analysis have studied the analysis of basic emotions and sentiment polarity independently. In other words, there are few corpora that are annotated with both basic emotions and sentiment polarity. Our dataset is the first large-scale corpus to annotate both of these emotion labels, and from both the writer's and reader's perspectives. In this paper, we analyze the relationship between basic emotion intensity and sentiment polarity on our dataset and report the results of benchmarking sentiment polarity classification.

    Scopus

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  • R&D of the KEK Linac Accelerator Tuning using Machine Learning 査読有り 国際誌

    Akihiro Hisano, Masako Iwasaki, Itsuka Satake, Masanori Sato, Hajime Nagahara, Yuta Nakashima, Noriko Takemura, Takashi Nakano

    International Conference on Accelerator and Large Experimental Physics Control Systems   2021年10月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

  • Characteristics of Adaptation in Undergraduate University Students Suddenly Exposed to Fully Online Education During the COVID-19 Pandemic 査読有り 国際誌

    Ishimaru D., Adachi H., Nagahara H., Shirai S., Takemura H., Takemura N., Mehrasa A., Higashino T., Yagi Y., Ikeda M.

    Frontiers in Psychiatry   12   2021年09月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    This study aimed to clarify the adaptation features of University students exposed to fully online education during the novel coronavirus disease 2019 (COVID-19) pandemic and to identify accompanying mental health problems and predictors of school adaptation. The pandemic has forced many universities to transition rapidly to delivering online education. However, little is known about the impact of this drastic change on students' school adaptation. This cross-sectional study used an online questionnaire, including assessments of impressions of online education, study engagement, mental health, and lifestyle habits. In total, 1,259 students were assessed. The characteristics of school adaptation were analyzed by a two-step cluster analysis. The proportion of mental health problems was compared among different groups based on a cluster analysis. A logistic regression analysis was used to identify predictors of cluster membership. P-values < 0.05 were considered statistically significant. The two-step cluster analysis determined three clusters: school adaptation group, school maladaptation group, and school over-adaptation group. The last group significantly exhibited the most mental health problems. Membership of this group was significantly associated with being female (OR = 1.42; 95% CI 1.06–1.91), being older (OR = 1.21; 95% CI 1.01–1.44), those who considered online education to be less beneficial (OR = 2.17; 95% CI 1.64–2.88), shorter sleep time on weekdays (OR = 0.826; 95% CI 0.683–.998), longer sleep time on holidays (OR = 1.21; 95% CI 1.03–1.43), and worse restorative sleep (OR = 2.27; 95% CI 1.81–2.86). The results suggest that academic staff should understand distinctive features of school adaptation owing to the rapid transition of the educational system and should develop support systems to improve students' mental health. They should consider ways to incorporate online classes with their lectures to improve students' perceived benefits of online education. Additionally, educational guidance on lifestyle, such as sleep hygiene, may be necessary.

    DOI: 10.3389/fpsyt.2021.731137

    Scopus

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  • Evaluating a Collaborative Learning Card Game for Pre-Intermediate Language Learners in Face-to-Face and Online Settings 査読有り

    Mehrasa Alizadeh, Tomomi Omae, Shizuka Shirai, Noriko Takemura

    Studies in e-Learning Language Education   2021年04月

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    担当区分:最終著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

  • Health indicator estimation by video-based gait analysis 査読有り 国際誌

    LIAO R., MORIWAKI K., MAKIHARA Y., MURAMATSU D., TAKEMURA N., YAGI Y.

    IEICE Transactions on Information and Systems ( 一般社団法人 電子情報通信学会 )   E104D ( 10 )   1678 - 1690   2021年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    In this study, we propose a method to estimate body composition-related health indicators (e.g., ratio of body fat, body water, and muscle, etc.) using video-based gait analysis. This method is more efficient than individual measurement using a conventional body composition meter. Specifically, we designed a deep-learning framework with a convolutional neural network (CNN), where the input is a gait energy image (GEI) and the output consists of the health indicators. Although a vast amount of training data is typically required to train network parameters, it is unfeasible to collect sufficient ground-truth data, i.e., pairs consisting of the gait video and the health indicators measured using a body composition meter for each subject. We therefore use a two-step approach to exploit an auxiliary gait dataset that contains a large number of subjects but lacks the ground-truth health indicators. At the first step, we pre-train a backbone network using the auxiliary dataset to output gait primitives such as arm swing, stride, the degree of stoop, and the body width - considered to be relevant to the health indicators. At the second step, we add some layers to the backbone network and fine-tune the entire network to output the health indicators even with a limited number of ground-truth data points of the health indicators. Experimental results show that the proposed method outperforms the other methods when training from scratch as well as when using an auto-encoder-based pre-training and fine-tuning approach; it achieves relatively high estimation accuracy for the body composition-related health indicators except for body fat-relevant ones.

    DOI: 10.1587/transinf.2020ZDP7502

    Scopus

    CiNii Article

    CiNii Research

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  • WRIME: A New Dataset for Emotional Intensity Estimation with Subjective and Objective Annotations 査読有り 国際誌

    Kajiwara T., Chu C., Takemura N., Nakashima Y., Nagahara H.

    NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference   2095 - 2104   2021年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    We annotate 17,000 SNS posts with both the writer’s subjective emotional intensity and the reader’s objective one to construct a Japanese emotion analysis dataset. In this study, we explore the difference between the emotional intensity of the writer and that of the readers with this dataset. We found that the reader cannot fully detect the emotions of the writer, especially anger and trust. In addition, experimental results in estimating the emotional intensity show that it is more difficult to estimate the writer’s subjective labels than the readers’. The large gap between the subjective and objective emotions implies the complexity of the mapping from a post to the subjective emotional intensities, which also leads to a lower performance with machine learning models.

    Scopus

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  • Improving topic modeling through homophily for legal documents 査読有り 国際誌

    Ashihara K., El Vaigh C.B., Chu C., Renoust B., Okubo N., Takemura N., Nakashima Y., Nagahara H.

    Applied Network Science   5 ( 1 )   2020年12月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Topic modeling that can automatically assign topics to legal documents is very important in the domain of computational law. The relevance of the modeled topics strongly depends on the legal context they are used in. On the other hand, references to laws and prior cases are key elements for judges to rule on a case. Taken together, these references form a network, whose structure can be analysed with network analysis. However, the content of the referenced documents may not be always accessed. Even in that case, the reference structure itself shows that documents share latent similar characteristics. We propose to use this latent structure to improve topic modeling of law cases using document homophily. In this paper, we explore the use of homophily networks extracted from two types of references: prior cases and statute laws, to enhance topic modeling on legal case documents. We conduct in detail, an analysis on a dataset consisting of rich legal cases, i.e., the COLIEE dataset, to create these networks. The homophily networks consist of nodes for legal cases, and edges with weights for the two families of references between the case nodes. We further propose models to use the edge weights for topic modeling. In particular, we propose a cutting model and a weighting model to improve the relational topic model (RTM). The cutting model uses edges with weights higher than a threshold as document links in RTM; the weighting model uses the edge weights to weight the link probability function in RTM. The weights can be obtained either from the co-citations or from the cosine similarity based on an embedding of the homophily networks. Experiments show that the use of the homophily networks for topic modeling significantly outperforms previous studies, and the weighting model is more effective than the cutting model.

    DOI: 10.1007/s41109-020-00321-y

    Scopus

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  • Warmer Environments Increase Implicit Mental Workload Even If Learning Efficiency Is Enhanced 査読有り 国際誌

    Kimura T., Takemura N., Nakashima Y., Kobori H., Nagahara H., Numao M., Shinohara K.

    Frontiers in Psychology   11   2020年04月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Climate change is one of the most important issues for humanity. To defuse this problem, it is considered necessary to improve energy efficiency, make energy sources cleaner, and reduce energy consumption in urban areas. The Japanese government has recommended an air conditioner setting of 28°C in summer and 20°C in winter since 2005. The aim of this setting is to save energy by keeping room temperatures constant. However, it is unclear whether this is an appropriate temperature for workers and students. This study examined whether thermal environments influence task performance over time. To examine whether the relationship between task performance and thermal environments influences the psychological states of participants, we recorded their subjective rating of mental workload along with their working memory score, electroencephalogram (EEG), heart rate variability, skin conductance level (SCL), and tympanum temperature during the task and compared the results among different conditions. In this experiment, participants were asked to read some texts and answer questions related to those texts. Room temperature (18, 22, 25, or 29°C) and humidity (50%) were manipulated during the task and participants performed the task at these temperatures. The results of this study showed that the temporal cost of task and theta power of EEG, which is an index for concentration, decreased over time. However, subjective mental workload increased with time. Moreover, the low frequency to high frequency ratio and SCL increased with time and heat (25 and 29°C). These results suggest that mental workload, especially implicit mental workload, increases in warmer environments, even if learning efficiency is facilitated. This study indicates integrated evidence for relationships among task performance, psychological state, and thermal environment by analyzing behavioral, subjective, and physiological indexes multidirectionally.

    DOI: 10.3389/fpsyg.2020.00568

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85083509426&origin=inward

  • Detecting learner drowsiness based on facial expressions and head movements in online courses 査読有り 国際誌

    Terai S., Shirai S., Alizadeh M., Kawamura R., Takemura N., Uranishi Y., Takemura H., Nagahara H.

    International Conference on Intelligent User Interfaces, Proceedings IUI   124 - 125   2020年03月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Drowsiness is a major factor that hinders learning. To improve learning efficiency, it is important to understand students' physical status such as wakefulness during online coursework. In this study, we have proposed a drowsiness estimation method based on learners' head and facial movements while viewing video lectures. To examine the effectiveness of head and facial movements in drowsiness estimation, we collected learner video data recorded during e-learning and applied a deep learning approach under the following conditions: (a) using only facial movement data, (b) using only head movement data, and (c) using both facial and head movement data.We achieved an average F1-macro score of 0.74 in personalized models for detecting learner drowsiness using both facial and head movement data.

    DOI: 10.1145/3379336.3381500

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85082166239&origin=inward

  • Exploring Pupillometry as a Method to Evaluate Reading Comprehension in VR-based Educational Comics 査読有り 国際誌

    Sakamoto K., Shirai S., Orlosky J., Nagataki H., Takemura N., Alizadeh M., Ueda M.

    Proceedings - 2020 IEEE Conference on Virtual Reality and 3D User Interfaces, VRW 2020   422 - 426   2020年03月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Ascertaining the level of reading comprehension in a learner is often a challenging task. Although written tests and self-evaluations can provide feedback as to whether an individual understands a particular topic, they are not real time, do not necessarily provide a full picture of the reader's comprehension, and can be subjective.In this paper, we present initial results of a study to determine better ways to evaluate a user's comprehension and understanding of educational comic books using pupillometry. Our system recreates the reading experience of an immunology comic book in virtual reality (VR), allows users to rate their comprehension of a particular section, and records eye data during the learning task. Through experiments, we explore the potential of this interface to facilitate learning and examine pupil metrics that might be used to automatically classify comprehension and understanding at the category (topic) level. We also discuss numerous design considerations that should be taken into account when designing future interfaces for evaluation of learning or comprehension.

    DOI: 10.1109/VRW50115.2020.00090

    Scopus

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  • 顔表情および頭部動作に基づくeラーニング時の覚醒度推定

    寺井 省吾, 川村 亮介, 白井 詩沙香, メラサ アリザデ, 武村 紀子, 浦西 友樹, 長原 一, 竹村 治雄

    第82回全国大会講演論文集   2020 ( 1 )   421 - 422   2020年02月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    オンライン教育やブレンディッドラーニングの普及に伴い,インターネット上で動画による講義を受講できるeラーニングの需要が高まってきている.eラーニングの課題として,学習者のエンゲージメントの維持があり、それを妨げる要因の一つとして眠気が挙げられる.眠気の検知に関する研究として,自動車分野では画像処理技術を用いた運転中のドライバーの眠気度合いの推定などが進められている.一方で,講義動画視聴中の学習者の覚醒度を推定する研究は未だ少ない.そこで,本研究では, eラーニング学習中のエンゲージメントの維持を目的として,講義動画視聴中の学習者の顔表情と頭部方向の変化に基づいて覚醒度を推定する手法を提案する.

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    その他リンク: http://id.nii.ac.jp/1001/00205777/

  • Legal Information as a Complex Network: Improving Topic Modeling Through Homophily 査読有り

    Ashihara K., Chu C., Renoust B., Okubo N., Takemura N., Nakashima Y., Nagahara H.

    Studies in Computational Intelligence   882 SCI   28 - 39   2020年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Topic modeling is a key component to computational legal science. Network analysis is also very important to further understand the structure of references in legal documents. In this paper, we improve topic modeling for legal case documents by using homophily networks derived from two families of references: prior cases and statute laws. We perform a detailed analysis on a rich legal case dataset in order to create these networks. The use of the reference-induced homophily topic modeling improves on prior methods.

    DOI: 10.1007/978-3-030-36683-4_3

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  • Constructing a public meeting corpus 査読有り 国際誌

    Tanaka K., Chu C., Ren H., Renoust B., Nakashima Y., Takemura N., Nagahara H., Fujikawa T.

    LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings   1934 - 1940   2020年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In this paper, we propose a method for constructing a large corpus about a century of public meetings in historical Australian newspapers, and analyze the constructed corpus. The corpus construction method is based on image processing and Optical Character Recognition (OCR). We digitize and transcribe texts of the specific topic of public meeting. Experiments show that our proposed method achieves a F-score of 71.5% with a high recall of 97.5% for corpus construction. This allows us to feed a content search tool for temporal and semantic content analysis.

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096584877&origin=inward

  • 公開集会記事からの情報抽出

    田中 昂志, 芦原 和樹, CHU Chenhui, 中島 悠太, 武村 紀子, 長原 一, 藤川 隆男

    人工知能学会全国大会論文集 ( 一般社団法人 人工知能学会 )   JSAI2020 ( 0 )   3Rin405 - 3Rin405   2020年01月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    <p>オーストラリアにおける世論形成,普遍的原理の歴史を読み解く鍵として公開集会記事が挙げられる. 公開集会記事から情報を抽出することで,オーストラリア史の新たな知見を得ることができると考えられる. したがって,本研究では公開集会記事のテキストからの情報抽出のためのデータを作成し,情報抽出手法を検討する. 人手で開催日時,場所,目的,招集を要求した人,招集した人,招集された人の情報をアノテーションし,118件の正解データを作成した. 情報抽出を機械読解のタスクとして定式化する手法を提案し,実験した結果,出力のいずれにおいても「答えがない」判定となった. これは公開集会データの95.20%が抽出対象と対応がとれていないことが原因であると考えられる.</p>

    DOI: 10.11517/pjsai.jsai2020.0_3rin405

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  • 追加ラベルを組み込んだ歩容特徴抽出器

    守脇 幸佑, 村松 大吾, 武村 紀子, 八木 康史

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 電子情報通信学会 )   119 ( 214 )   31 - 35   2019年10月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • 学習効率が向上しても熱環境は潜在的精神負荷を増大させる

    木村 司, 武村 紀子, 中島 悠太, 小堀 寛和, 長原 一, 沼尾 正行, 篠原 一光

    日本心理学会大会発表論文集 ( 公益社団法人 日本心理学会 )   83 ( 0 )   1B-052 - 1B-052   2019年09月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    DOI: 10.4992/pacjpa.83.0_1b-052

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    その他リンク: https://www.jstage.jst.go.jp/article/pacjpa/83/0/83_1B-052/_pdf

  • 大規模歩行映像データベースの構築とその歩行映像解析への応用

    槇原靖,村松大吾,武村紀子,モハマド ザシム ウディン,徐遅,越後富夫,チュン タン ゴ,李想,荻岳仁,八木康史

    画像ラボ   2019年03月

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    記述言語:日本語   掲載種別:記事・総説・解説・論説等(商業誌、新聞、ウェブメディア)

  • セキュリティ 大規模歩行映像データベースの構築とその歩行映像解析への応用

    槇原 靖, 村松 大吾, 武村 紀子, モハマド ザシム ウディン, 徐 遅, 越後 富夫, チュン タン ゴ, 李 想, 荻 岳仁, 八木 康史

    画像ラボ / 画像ラボ編集委員会 編 ( 日本工業出版 )   30 ( 3 )   11 - 17   2019年03月

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    記述言語:日本語   掲載種別:記事・総説・解説・論説等(学術雑誌)

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  • 深層学習による高精度歩容認証

    武村紀子,白神康平,槇原靖,村松大吾,越後富夫,八木康史

    画像ラボ   2019年01月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(商業誌、新聞、ウェブメディア)

  • Pseudo normal image generation for anomaly detection on road surface 査読有り 国際誌

    Mori N., Takemura N., Yagi Y.

    Proceedings of SPIE - The International Society for Optical Engineering   11172   2019年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In Japan, the age-related deterioration of many public roads, which were constructed in the 1960s, is demanding maintenance solutions. We propose a convolutional neural network (CNN)-based method to convert the original image to a pseudo normal road surface image. The converter selectively replaces only the abnormal data of an image with pixels corresponding to normal features, thereby creating an output image without abnormal parts. We aim to detect anomalies on the road surface by calculating the difference between a raw input image and the generated PNI image. Our experimental results confirm the effectiveness and usefulness of our method.

    DOI: 10.1117/12.2522245

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85070211399&origin=inward

  • Gait-Based Age Estimation Using a DenseNet 査読有り 国際誌

    Sakata A., Makihara Y., Takemura N., Muramatsu D., Yagi Y.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   11367 LNCS   55 - 63   2019年01月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Human age is one of important attributes for many potential applications such as digital signage, customer analysis, and gait-based age estimation is promising particularly for surveillance scenarios since it can be available at a distance from a camera. We therefore proposed a method of gait-based age estimation using a deep learning framework to advance the state-of-the-art accuracy. Specifically, we employed DenseNet as one of state-of-the-art network architectures. While the previous method of gait-based age estimation using a deep learning framework was evaluated only with a small-scale gait database, we evaluated the proposed method with OULP-Age, the world’s largest gait database comprising more than 60,000 subjects with age range from 2 to 90 years old. Consequently, we demonstrated that the proposed method outperform existing methods based on both conventional machine learning frameworks for gait-based age estimation and a deep learning framework for gait recognition.

    DOI: 10.1007/978-3-030-21074-8_5

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85068445417&origin=inward

  • STHOG特徴に基づく歩行者照合のCNNによる高精度化

    柏本 雄士朗, 村松 大吾, 武村 紀子, 八木 康史

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 電子情報通信学会 )   118 ( 405 )   11 - 16   2019年01月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • CNNに基づいた歩容クラス識別における中間出力の個人性評価

    守脇 幸佑, 村松 大吾, 武村 紀子, 八木 康史

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 電子情報通信学会 )   118 ( 236 )   45 - 49   2018年10月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • 歩容による推定年齢と健康年齢に関する考察

    阪田 篤哉, 西川 博文, 武村 紀子, 槇原 靖, 村松 大吾, 八木 康史

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 電子情報通信学会 )   118 ( 236 )   39 - 44   2018年10月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • 深層学習を用いた観測方向の違いに頑健な高精度歩容認証

    武村紀子,槇原康史,村松大吾,越後富夫,八木康史

    画像ラボ   2018年08月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(商業誌、新聞、ウェブメディア)

  • Tracking abnormalities in video capsule endoscopy via convolutional neural networks by intra-frame training 査読有り

    Yanagawa Y., Echigo T., Miyazaki Y., Takemura N., Yagi Y.

    Transactions of the Japanese Society for Artificial Intelligence ( 一般社団法人 人工知能学会 )   33 ( 6 )   C-I33_1 - 12   2018年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    Tracking precisely of abnormalities in the gastrointestinal tract is useful for preparing sample image sequences on educational training for medical diagnose on endoscopy. While the gastrointestinal wall deforms continuously in an unpredictable manner, however, abnormalities without distinctive features make it difficult to track over continuous frames. To address this problem, the proposed method employs Convolutional neural networks (CNN) for tracking lesion area. Conventionally, CNN for tracking requires a large amount of sample data for preliminary learning. The state-of-arts tracking methods using CNN are premised on preliminary learning on data similar to target images given a large number of correct answer labels. On the other hand, the proposed method are not required preliminary learning using similar data. The image components in the marked region at the starting frame is similar to components at the only same position, but different between them depending on the degree of overlapped area. Furthermore, in the successive frame, the components in the previous region is similar to them in the identified area. Therefore, similarity can be learned in the previous frame, called it as an intra-frame training. This paper describes the method for tracking an abnormal region by using CNN based on training overlap rates between the abnormal region and local scanning one with the same size on the starting intra-frame. Furthermore, network parameters are transformed from training the similar regions on the continuous frame additionally. We demonstrate the efficiency of the proposed approach using eight common types of gastrointestinal abnormality.

    DOI: 10.1527/tjsai.C-I33

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  • Wonder What Women's Happiness Is

    Takemura N.

    Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers   72 ( 7 )   566 - 568   2018年01月

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    担当区分:筆頭著者, 最終著者, 責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

    DOI: 10.3169/ITEJ.72.566

    Scopus

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  • 生活支援 深層学習による高精度歩容認証

    武村 紀子, 白神 康平, 槇原 靖, 村松 大吾, 八木 康史, 越後 富夫

    画像ラボ / 画像ラボ編集委員会 編 ( 日本工業出版 )   29 ( 1 )   40 - 48   2018年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(学術雑誌)

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  • 多視点大規模歩容データベースの構築と異なる視点における歩容認証の性能評価

    武村 紀子, 槇原 靖, 村松 大吾, 越後 富夫, 八木 康史

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 電子情報通信学会 )   116 ( 527 )   81 - 86   2017年03月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • 顔画像における強度の時空間変化特徴に基づく疲労推定 査読有り

    武村 紀子

    電子情報通信学会論文誌 B   J100-B   1014 - 1022   2017年01月

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    担当区分:責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

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  • 畳み込みニューラルネットワークを用いた視点変化に頑健な歩容認証 査読有り

    武村紀子,白神康平,槇原靖,村松大吾,越後富夫,八木康史

    電子情報通信学会和文論文誌   2016年12月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • A Typing Assist System Considering Involuntary Hand Tremor 査読有り

    Kai Wang, Noriko Takemura, Daisuke Iwai, Kosuke Sato

    日本バーチャルリアリティ学会論文誌   2016年09月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

  • 照度変動に起因する無意識的行動に基づく快不快推定

    菊川 剛, 武村 紀子, 佐藤 宏介

    システム制御情報学会研究発表講演会講演論文集 ( システム制御情報学会 )   60   4p   2016年05月

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    記述言語:日本語   掲載種別:研究論文(大学,研究機関等紀要)

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  • 「日常生活で使える生体計測システム」研究・開発の要点 第2回

    大須賀美恵子,才脇直樹,武村紀子

    人間生活工学   2016年03月

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    担当区分:最終著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(大学・研究所紀要)

  • 「日常生活で使える生体計測システム」研究・開発の要点(第2回)

    大須賀 美恵子, 才脇 直樹, 武村 紀子

    人間生活工学 = Journal of human life engineering ( 人間生活工学研究センター )   17 ( 1 )   33 - 38   2016年03月

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    担当区分:最終著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(学術雑誌)

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  • A Typing Assist System Considering Involuntary Hand Tremor 査読有り

    Wang Kai, Takemura Noriko, Iwai Daisuke, Sato Kosuke

    日本バーチャルリアリティ学会論文誌 ( 特定非営利活動法人 日本バーチャルリアリティ学会 )   21 ( 2 )   227 - 233   2016年01月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)

    <p>Typing keyboard is a very common activity, but is difficult for the people with hand tremor. Because hand tremor featured with involuntary hand shaking affects precise hand movements and finger control, and most of keyboards have small keys and close key arrangement, tremor hands usually fail to type the desired key of keyboard. In this paper, we proposed a typing assisted system to support hand tremor sufferers correctly typing with the ordinary physical keyboard under the condition of hand tremor movements. The system includes the novel technologies of finger stabilization and virtual key remapping, which contribute to estimate user's wanted key from finger involuntary shaking and to make sure the key correctly input in the case of finger actually touching the wrong key of keyboard. The experiment results showed that tremor hand typing with the proposed system can significantly reduce the input error rate and the time wasted on correcting error input, comparing with tremor hand typing keyboard directly.</p>

    DOI: 10.18974/tvrsj.21.2_227

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  • 日常生活で使える生体計測システム」研究・開発の要点 第1回

    大須賀美恵子,才脇直樹,武村紀子

    人間生活工学   2015年09月

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    担当区分:最終著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(大学・研究所紀要)

  • 「日常生活で使える生体計測システム」研究・開発の要点(第1回)

    大須賀 美恵子, 才脇 直樹, 武村 紀子

    人間生活工学 = Journal of human life engineering ( 人間生活工学研究センター )   16 ( 2 )   38 - 42   2015年09月

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    担当区分:最終著者   記述言語:日本語   掲載種別:記事・総説・解説・論説等(学術雑誌)

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  • 発話時の表情変化に基づく疲労推定

    川村 亮介, 武村 紀子, 佐藤 宏介

    システム制御情報学会研究発表講演会講演論文集 ( システム制御情報学会 )   59   4p   2015年05月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • Evaluation and fair comparison of human tracking methods with PTZ cameras 査読有り 国際誌

    Yildiz A., Takemura N., Iwai Y., Sato K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   9179   153 - 161   2015年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Evaluation and comparison of methods, repeatability of experiments, and availability of data are the dynamics driving science forward. In computer vision, a database with ground-truth information enables fair comparison and facilitates rapid improvement of methods in a particular topic. Being a high-level discipline, Human-Computer Interaction (HCI) systems rises on numerous computer vision building blocks, including eye-gaze localization, human localization, action recognition, behavior analysis etc. using mostly active systems employing lasers, projectors, infrared scanners, pan-tilt-zoom cameras and other various active sensors. In this research, we focus on fair comparison of human tracking methods with active (PTZ) cameras. Although there are databases on human tracking, no specific database is available for active (pan-tilt-zoom) camera human tracking. This is because active camera experiments are not repeatable, as camera views depend on previous decisions made by the system. Here, we address the above problem of systematical evaluation of active camera tracking methods and present a survey of their performances.

    DOI: 10.1007/978-3-319-21067-4_17

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  • Tracking people with active cameras using variable time-step decisions 査読有り 国際誌

    Yildiz A., Takemura N., Hori M., Iwai Y., Sato K.

    IEICE Transactions on Information and Systems ( 一般社団法人 電子情報通信学会 )   E97-D ( 8 )   2124 - 2130   2014年08月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    In this study, we introduce a system for tracking multiple people using multiple active cameras. Our main objective is to surveille as many targets as possible, at any time, using a limited number of active cameras. In our context, an active camera is a statically located pan-tiltzoom camera. In this research, we aim to optimize the camera configuration to achieve maximum coverage of the targets. We first devise a method for efficient tracking and estimation of target locations in the environment. Our tracking method is able to track an unknown number of targets and easily estimate multiple future time-steps, which is a requirement for active cameras. Next, we present an optimization of camera configuration with variable time-step that is optimal given the estimated object likelihoods for multiple future frames. We confirmed our results using simulation and real videos, and show that without introducing any significant computational complexities, it is possible to use active cameras to the point that we can track and observe multiple targets very effectively. Copyright © 2014 The Institute of Electronics, Information and Communication Engineers.

    DOI: 10.1587/transinf.E97.D.2124

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  • A tabletop interface using fingernail images and real object recognition 査読有り 国際誌

    Hara K., Takemura N., Iwai Y., Sato K.

    Electronics and Communications in Japan   97 ( 7 )   31 - 38   2014年07月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    SUMMARY A variety of research on tabletop interfaces has been reported in the last decade. In a tabletop system, the difference in operation between digital media and physical media such as paper gives an unsatisfactory experience and disturbs their comfortable simultaneous use. For users to be satisfied, they must be able to operate the digital and physical media seamlessly. In this paper, we propose a tabletop interface system that allows users to operate digital media intuitively by using gesture recognition. The proposed table can capture an image of an object on the table by utilizing press gesture recognition from images of a user's fingernail based on support vector machine (SVM), and can acquire digital content from digital paper by utilizing a shake gesture of the device. The evaluation experiments show that the proposed system recognizes a user's finger state with high accuracy and that the users can intuitively operate the table without any awareness of data transmission. © 2014 Wiley Periodicals, Inc.

    DOI: 10.1002/ecj.11547

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  • ユーザインタフェースのためのアンビエントパターン計測技術

    岩井大輔,武村紀子,佐藤宏介

    計測と制御   2014年07月

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    記述言語:日本語   掲載種別:記事・総説・解説・論説等(大学・研究所紀要)

  • Construction of an interpersonal interaction system using a real image-based avatar 査読有り

    Hara K., Hori M., Takemura N., Iwai Y., Sato K.

    IEEJ Transactions on Electronics, Information and Systems ( 一般社団法人 電気学会 )   134 ( 1 )   102 - 111   2014年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    We propose a method for constructing an interpersonal interaction system using a real image-based avatar. Humancomputer interaction is important when we communicate with computers. As a medium of an interpersonal interaction, communication robots are used commonly in the real world and CG avatar is used in the virtual world. On behalf of the communication robots, android robots that have a similar appearance to an actual person can effectively transfer the human presence. On the other hand, CG avatar has advantages of a cost and installation space as compared to communication robots. When we use a CG avatar for a communication, it is important to increase the reality of a speaker. In this paper, we construct a prototype of an interpersonal interaction system using a real image-based avatar. By generating the avatar from captured images, we can have a high realistic sensation similar to the interpersonal communication system such as a video conference system. In the proposed method, additionally, the movement of the avatar is smoothed by generating interpolated images. The interpolated images are generated by approximating avatar's each body part as an ellipsoid, using user's posture information. To verify the validity of the system, we have conducted the experiments of subjective evaluation. © 2014 The Institute of Electrical Engineers of Japan.

    DOI: 10.1541/ieejeiss.134.102

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  • Tracking people with active cameras via Bayesian risk formulation 査読有り

    Yildiz A., Takemura N., Iwai Y., Sato K.

    IEEJ Transactions on Electronics, Information and Systems ( 一般社団法人 電気学会 )   134 ( 6 )   870 - 877   2014年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    In this study, we introduce a system for tracking multiple people using multiple active cameras. Our main objective is to capture as many targets as possible at any time, using a limited number of active cameras. In our context, an active camera is a statically located pan-tilt-zoom camera. The use of active cameras for tracking has not been thoroughly researched, because it is relatively easier to set up and use static cameras. However, there are many properties of active cameras that we can exploit. Our results show that an approximately two-fold increase in relative accuracy can be achieved without any significant increases in computational costs. Our main contributions include removing the necessity for the individual detection of each tracked target, estimating the future states of the system using a simplified fluid simulation, and finally unifying the active camera tracking method using a minimum risk formulation. We also improved the accuracy by developing an efficient method for attracting cameras towards targets located far away from the present camera configuration. © 2014 The Institute of Electrical Engineers of Japan.

    DOI: 10.1541/ieejeiss.134.870

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  • Regression based trajectory learning and prediction for human motion 査読有り 国際誌

    Yildiz A., Takemura N., Iwai Y., Sato K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   8334   193 - 202   2014年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    This paper presents a method for learning and predicting human motion in closed environments. Many surveillance, security, entertainment and smart-home systems require the localization of human subjects and the prediction of their future locations in the environment. Traditional tracking methods employ a linear motion model for human motion. However, for complex scenarios, where motion trajectory is dependent on the structure of the environment, linear motion model is insufficient. In this paper, we present a behavior-aware method for learning and predicting human motion in closed environments. Our method adaptively combines traditional linear motion model, where there is not much behavioral data, with the learned motion model, where there is sufficient data available. We present the mathematical and implementation details along with the experimental results to show the effectiveness of our method.

    DOI: 10.1007/978-3-642-53926-8_18

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  • Detection of unconscious facial reactions to uncomfortable illumination 査読有り

    Kitamura K., Takemura N., Iwai Y., Sato K.

    IEEJ Transactions on Electronics, Information and Systems ( 一般社団法人 電気学会 )   134 ( 2 )   218 - 224   2014年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    In this study, we investigated expressive facial reactions in response to changes in the visual environment and their automatic extraction from sensors, in order to construct a comfortable level of illumination in personal living spaces. We conducted an experiment that showed that expressive facial reactions occur when illumination in the visual environment changes. We captured facial images and manually classified them as expressing or not expressing discomfort. We then conducted a second experiment that showed that automatic image processing can be used to extract and identify these expressive facial reactions. We extracted facial features and used a support vector machine to learn the classification in this experiment. © 2014 The Institute of Electrical Engineers of Japan.

    DOI: 10.1541/ieejeiss.134.218

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  • ユーザインタフェースのためのアンビエントパターン計測技術

    岩井 大輔, 武村 紀子, 佐藤 宏介

    計測と制御 ( 公益社団法人 計測自動制御学会 )   53 ( 7 )   599 - 604   2014年01月

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    記述言語:日本語   掲載種別:記事・総説・解説・論説等(学術雑誌)

    DOI: 10.11499/sicejl.53.599

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  • Tracking people with active cameras 査読有り 国際誌

    Yildiz A., Takemura N., Iwai Y., Sato K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   8008 LNCS ( PART 5 )   270 - 279   2013年07月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In this paper, we introduce a novel method on tracking multiple people using multiple active cameras. The aim is to capture as many targets as possible at any time using a limited number of active cameras. In our context, an active camera is a statically located PTZ (pan-tilt-zoom) camera. Using active cameras for tracking is not researched thoroughly, since it is relatively easier to use increased number of fully static cameras. However, we believe this is costly and a deeper research on the employment of active cameras is necessary. Our contributions include the removal of necessity for the detection of each person individually in an efficient way and estimating the future states of the system using a simplified fluid simulation. © 2013 Springer-Verlag.

    DOI: 10.1007/978-3-642-39342-6_30

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  • k近傍法に基づく予測を用いた人物追跡のための複数エージェントの経路計画法 査読有り

    武村紀子,中村泰,石黒浩

    計測自動制御学会論文集   2013年05月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • <i>k</i>近傍法に基づく予測を用いた人物追跡のための複数エージェントの経路計画法 査読有り

    武村 紀子, 中村 泰, 石黒 浩

    計測自動制御学会論文集 ( 公益社団法人 計測自動制御学会 )   49 ( 5 )   553 - 559   2013年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

    This paper deals with a multi-agent path planning problem for tracking humans in order to obtain detail information such like human behavior and characteristics. To achieve this, paths of agents is planned based on similarity between the predicted intensity of humans positions and the agents' field of view in the future. The positions of humans are predicted by a <i>k</i>-Nearest Neighbor-based method which allows to predict complicated human movements in a real environment. The number of steps of the planned path is determined according to the consistency between the current prediction and the previous prediction of the future human positions to avoid the path planning using less reliable predictions. We conducted computer simulations and results showed that agents can follow human trajectories observed in a real environment, i.e., concourse of a station by our path planning method.

    DOI: 10.9746/sicetr.49.553

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  • A path-planning method for human-tracking agents based on long-term prediction 査読有り 国際誌

    Takemura N., Nakamura Y., Matsumoto Y., Ishiguro H.

    IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews   42 ( 6 )   1543 - 1554   2012年12月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    This paper deals with a multiagent path-planning problem where several robots track humans to obtain detailed information on human behaviors and characteristics. For this, agents' paths are planned on the basis of the similarity between the predicted positions of humans and the agents' field of view. The long-horizon path planned on the basis of an accurate long-horizon prediction improves the tracking performance. However, it requires heavy computation and is less useful if the prediction is inaccurate. Since the accuracy of the prediction depends on the situation, the prediction term is determined by the similarity between the current and previous predictions. The results of computer simulation showed that our path-planning method works well for trajectories of humans in a dynamic environment by changing the horizon length of the path planning. © 1998-2012 IEEE.

    DOI: 10.1109/TSMCC.2012.2203801

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  • 室内照明制御のための生体ゆらぎ理論を用いた遮蔽度推定 査読有り

    松本裕樹,武村紀子,中村泰,岩井儀雄,石黒浩

    計測自動制御学会論文集   2012年11月

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    担当区分:責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • Automatic detection of unconscious reactions to illuminance changes in illumination 査読有り 国際誌

    Kitamura K., Takemura N., Iwai Y., Sato K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7378 LNCS   134 - 143   2012年08月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    In this study, we investigated expressive facial reactions in response to changes in the visual environment and their automatic extraction from sensors, in order to construct a comfortable level of illumination in personal living spaces. We conducted an experiment that showed that expressive facial reactions occur when illumination in the visual environment changes. We captured facial images and manually classified them as expressing or not expressing discomfort. We then conducted a second experiment that showed that automatic image processing can be used to extract and identify these expressive facial reactions. We extracted facial features and used a support vector machine to learn the classification in this experiment. © 2012 Springer-Verlag.

    DOI: 10.1007/978-3-642-31567-1_13

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  • A tabletop interface using nail images and real object recognition 査読有り

    Hara K., Takemura N., Iwai Y., Sato K.

    IEEJ Transactions on Electronics, Information and Systems ( 一般社団法人 電気学会 )   132 ( 8 )   1340 - 1346   2012年01月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    Many researches and developments of table-top interface have been proposed in the last decade. In a tabletop system, the difference of operations between the digital media and the physical media like a paper gives us unsatisfactory experience and disturbs a comfortable simultaneous using of them. It is required for user satisfaction that the user can operate the digital and physical media seamlessly. In this paper, we propose a table-top interface system that allows users to operate digital media intuitively by using gesture recognition. The proposed table can capture an image of the object on the table by press gesture recognition from users' nail images based on SVM, and can acquire a digital content from a digital paper reader by shake gesture of the device. The evaluation experiments show that the proposed system recognizes users' finger state with higher accuracy and the users can intuitively operate the table without awareness of the data transmission. © 2012 The Institute of Electrical Engineers of Japan.

    DOI: 10.1541/ieejeiss.132.1340

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  • 室内照明制御のための生体ゆらぎ理論を用いた遮蔽度推定 査読有り

    松本 裕樹, 武村 紀子, 中村 泰, 岩井 儀雄, 石黒 浩

    計測自動制御学会論文集 ( 公益社団法人 計測自動制御学会 )   48 ( 11 )   740 - 744   2012年01月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)

    In this paper, we propose a control method for multiple lights to provide a comfortable living environment for all residents in it. It is not easy to configure the illuminance environment because of dynamic changes in the environment which are induced by disturbances such as obstacles of light and the external light. In this study, we employ the light occlusion rate parameter to estimate the illuminance situation and the voltage of light is controlled based on the estimated value. Furthermore, we employ a control rule based on the theory of biological fluctuation to make the estimation more precisely. Experimental results show that our method works well and the occlusion parameter can be estimated stably.

    DOI: 10.9746/sicetr.48.740

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  • 照度変動に対する無意識下での表出行動検出

    北村 謙典, 武村 紀子, 岩井 儀雄

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 一般社団法人電子情報通信学会 )   111 ( 378 )   145 - 150   2012年01月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • 対人インタラクションアバタの作成に必要な再生技術の検討

    原 健太, 武村 紀子, 岩井 儀雄

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 一般社団法人電子情報通信学会 )   111 ( 379 )   227 - 232   2012年01月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

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  • A path planning method for human tracking agents using variable-term prediction based on dynamic k-nearest neighbor algorithm 査読有り 国際誌

    Takemura N., Nakamura Y., Ishiguro H.

    IEEE International Conference on Intelligent Robots and Systems   2867 - 2872   2011年12月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    This paper deals with a multi-agent path planning problem for tracking humans in order to obtain detail information such like human behavior and characteristics. To achieve this, paths of agents are planned based on similarity between the predicted positions of humans and agents' field of views, and the path length in the path planning is determined according to the consistency between the current prediction and the previous prediction of the future human positions. We conducted computer simulations and results showed that our path planning method works well for trajectories of human in a real environment. © 2011 IEEE.

    DOI: 10.1109/IROS.2011.6048133

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  • Extracting interval distribution of human interactions 査読有り 国際誌

    Kimura R., Takemura N., Iwai Y., Sato K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7088 LNCS ( PART 2 )   262 - 273   2011年11月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Recently, activity support systems that enable dialogue with humans have been intensively studied owing to the development of various sensors and recognition technologies. In order to enable a smooth dialogue between a system and a human user, we need to clarify the rules of dialogue, including how utterances and motions are interpreted among human users. In conventional study on dialogue analysis, duration between the time when someone finishes an utterance and the time when another human starts the next utterance were analyzed. In a real dialogue between humans, however, there are sufficient intervals between an utterance and a visually observable motion such as bowing and establishing eye-contact; the facilitation of communication and cooperation seem to depend on these intervals. In our study, we analyze interactions that involve utterances and motions at a reception scenario by resolving motions into motion primitives (a basic unit of motion). We also analyze the timing of utterances and motions in order to structure dialogue behaviors. Our result suggest that a structural representation of interaction can be useful for improving the ability of activity support systems to interact and support human dialogue. © 2011 Springer-Verlag.

    DOI: 10.1007/978-3-642-25346-1_24

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=82155197256&origin=inward

  • Table-top interface using fingernail images and real object recognition 査読有り 国際誌

    Hara K., Takemura N., Iwai Y., Sato K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   7040 LNCS   21 - 30   2011年11月

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    Many researchers have proposed the development of table-top interfaces in the last decade. In a table-top system, for user satisfaction, they must be able to operate digital and analog media seamlessly. In this paper, we propose a table-top interface system that allows users to intuitively operate digital media by gesture recognition. The proposed system can capture the image of an object placed on the table by recognizing pressing gestures from fingernail images, and can transfer digital content by recognizing user's shaking gestures. The evaluation experiments show that users can intuitively operate the proposed system without being aware of the data transmission. © 2011 Springer-Verlag.

    DOI: 10.1007/978-3-642-25167-2_3

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=81855212605&origin=inward

  • 人物対話行動における応答時間分布抽出

    木村綾平, 武村紀子, 岩井儀雄, 佐藤宏介

    画像の認識・理解シンポジウム(MIRU2011)論文集   ( 2011 )   639 - 645   2011年07月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    CiNii Article

    CiNii Research

    その他リンク: http://id.nii.ac.jp/1001/00077732/

  • 快適な光環境構築のための表出行動抽出

    北村謙典, 武村紀子, 岩井儀雄, 佐藤宏介

    画像の認識・理解シンポジウム(MIRU2011)論文集   2011   646 - 653   2011年07月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    本研究では,ユーザの身体動作からその心理状態の変化を解釈し,それらを指標とする自律的な快適環境構築システムを提案する.本論文では,提案システムを構築するに際して,居住空間における光環境に着目し,「環境に不快と感じる照度変化が生じた際,ユーザにいかなる表出行動が観測されるか」という問題に焦点を当て,行動分析を行った.まず予備実験として,3名の被験者に対して様々なパターンの照度変化を与え,表出行動が存在すること,及び照度変化のパターンや学習による差異を確認した.次いで,11名の被験者に対して行動抽出実験を行い,その結果,頭部姿勢・視線方向の変化,瞬き,口の動き,本の角度調節等を表出行動として抽出した.

    CiNii Article

    CiNii Research

    その他リンク: http://id.nii.ac.jp/1001/00077733/

  • Human tracking with variable prediction steps based on Kullback-Leibler divergence 査読有り 国際誌

    Takemura N., Nakamura Y., Matsumoto Y., Ishiguro H.

    Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10   395 - 398   2010年12月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    This paper deals with a path planning problem for tracking humans in order to obtain detail information about human behavior and characteristics. In our method, path planning is performed based on Kullback-Leibler (KL) divergence between the predicted distribution of all human positions and the intensity of field of view of agents. The number of prediction steps is determined according to the consistency of the prediction. Experimental results show that when prediction of human movement is accurate, the long-term prediction is useful for the path planning. On the other hand, when prediction is inaccurate, long-term prediction might not be useful. Our path planning method works well even under changing circumstances by changing the number of the prediction length. © 2010 ISAROB.

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84866718865&origin=inward

  • A path planning method for human tracking agents using variable-term prediction 査読有り 国際誌

    Takemura N., Nakamura Y., Matsumoto Y., Ishiguro H.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   6354 LNCS ( PART 3 )   407 - 410   2010年11月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    This paper deals with a multi-agent path planning problem for tracking humans. Path of agents is planned based on the similarity between the prediction of the intensity of humans existing and the intensity of field of view of agents. Since the prediction is not always accurate, we proposed the an path planning method method where prediction length is varied based on the reliability of the prediction. We conducted computer simulation and results showed that our path planning method works well even under changing circumstances. © 2010 Springer-Verlag Berlin Heidelberg.

    DOI: 10.1007/978-3-642-15825-4_53

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78049429891&origin=inward

  • Human tracking with variable prediction steps based on Kullback-Leibler divergence 招待有り 査読有り 国際誌

    Takemura N., Nakamura Y., Matsumoto Y., Ishiguro H.

    Artificial Life and Robotics   15 ( 1 )   111 - 116   2010年09月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)

    This article deals with a path-planning problem in tracking humans in order to obtain detailed information about human behavior and characteristics. In our method, path planning is performed based on Kullback-Leibler (KL) divergence between the predicted distribution of all human positions and the intensity. The number of steps predicted is determined according to the consistency of the prediction. Experimental results show that when the prediction of human movement is accurate, long-term prediction is useful for path planning. On the other hand, when prediction is inaccurate, long-term prediction might not be useful. Our path-planning method works well even under changing circumstances by changing the length of the predictions. © 2010 International Symposium on Artificial Life and Robotics (ISAROB).

    DOI: 10.1007/s10015-010-0777-8

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77956115799&origin=inward

  • 2P1-B24 長期予測に基づいた人物追跡のための複数エージェントの経路計画法

    武村 紀子, 中村 泰, 松本 吉央, 石黒 浩

    ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人 日本機械学会 )   2010 ( 0 )   _2P1-B24_1 - _2P1-B24_4   2010年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    This paper deals with a multi-agent path planning problem for tracking humans in order to obtain detail information such like human behavior and characteristics. To achieve this, path of agents is planned based on a clustering method, that is, agents follow paths which minimize Kullback-Leibler (KL) divergence between the intensity of humans existing and the intensity of field of view of agents calculated from predicted human positions and planned paths of agents. When prediction of human movement is accurate, the long-term prediction of human position would improve the performance. Since the prediction is not always accurate, the number of prediction steps is determined according to the difference between the current prediction and the previous prediction of the future human position. We conducted computer simulation and results showed that our path planning method works well even under changing circumstances.

    DOI: 10.1299/jsmermd.2010._2p1-b24_1

    CiNii Article

    CiNii Research

    その他リンク: https://www.jstage.jst.go.jp/article/jsmermd/2010/0/2010__2P1-B24_1/_pdf

  • 可変長予測に基づく人物追跡

    武村紀子, 中村泰, 松本吉央, 石黒浩

    平成21年度情報処理学会関西支部支部大会講演論文集   2009   2009年09月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    本研究では効率の良い人物追跡を行うため,人物の位置予測に基づいた移動エージェントの経路計画問題を扱う.人物の位置予測の容易さに応じて予測ステップ数を変化させることによって,環境の変化にロバストな人物追跡が可能となった.

    CiNii Article

    CiNii Research

    その他リンク: http://id.nii.ac.jp/1001/00071690/

  • 2A1-F13 広域監視のための複数エージェントの経路計画

    武村 紀子, 中村 泰, 小泉 智史, 松本 吉央, 石黒 浩

    ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人 日本機械学会 )   2009 ( 0 )   _2A1-F13_1 - _2A1-F13_4   2009年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    This paper describes an efficient solution to a multi-agent path planning problem where a relatively small number of agents track many persons for surveillance purposes. Since search space for path planning is enormous, we developed a meta-heuristics-based planner where the optimization process changes according to the Kullback-Leibler Divergence between the current and the previous prediction of the state transition. We conducted simulated experiments and shows our planning method is considered to be effective.

    DOI: 10.1299/jsmermd.2009._2a1-f13_1

    CiNii Article

    CiNii Research

    その他リンク: https://www.jstage.jst.go.jp/article/jsmermd/2009/0/2009__2A1-F13_1/_pdf

  • 2P2-B19 複数人物追跡のための複数カメラの注視点選択(ロボットビジョン)

    武村 紀子, 三浦 純, 石黒 浩

    ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人 日本機械学会 )   2008 ( 0 )   _2P2-B19_1 - _2P2-B19_4   2008年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    This paper describes an efficient solution to a multi-camera view planning problem. We deal with the case where a relatively small number of active cameras track many persons for surveillance purposes. Planning camera view is therefore one of the important issues in realizing a competent surveillance system. In our previous paper, we formulated the planning problem as a combinatorial optimization problem. Since its search space is very large, we developed a multistart local search (MLS)-based planner with non-linear programming for initial solution generation. The method is efficient enough to be used on-line. We apply the method to the problem of selecting several focused area in the image sequence from a fixed camera, which simulates the multi-camera view planning problem. Considering the success ratio of CamShift-based tracking, our planning method is considered to be sufficiently effective.

    DOI: 10.1299/jsmermd.2008._2p2-b19_1

    CiNii Article

    CiNii Research

    その他リンク: https://www.jstage.jst.go.jp/article/jsmermd/2008/0/2008__2P2-B19_1/_pdf

  • View planning of multiple active cameras for wide area surveillance 査読有り 国際誌

    Takemura N., Miura J.

    Proceedings - IEEE International Conference on Robotics and Automation   3173 - 3179   2007年11月

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    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)

    This paper describes a view planning of multiple cameras for tracking multiple persons for surveillance purposes. When only a few active cameras are used to cover a wide area, planning their views is an important issue in realizing a competent surveillance system. We develop a multi-start local search (MLS)-based planning method which iteratively selects fixation points of the cameras by which the expected number of tracked persons is maximized. Considering the fact that a person's motion can be estimated with its intermittent observations, we set a criterion which encourages frequent shifts of fixation points and develop a procedure for generating promising initial solutions for MLS. The method is shown to outperform the other approaches. We then modify the method such that it dynamically divides the cameras into mutually independent groups and determines fixation points within each group. The modified method is comparable to the original one with a much lower planning cost. © 2007 IEEE.

    DOI: 10.1109/ROBOT.2007.363962

    Scopus

    その他リンク: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=36349024648&origin=inward

  • 多スタート局所探索法を用いた多数人物追跡のための複数能動カメラの同時視線プランニング 査読有り

    武村紀子,三浦純

    日本ロボット学会誌   2007年11月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

  • 多スタート局所探索法を用いた多数人物追跡のための複数能動カメラの同時視線プランニング 査読有り

    武村 紀子, 三浦 純

    日本ロボット学会誌 ( 一般社団法人 日本ロボット学会 )   25 ( 8 )   1226 - 1233   2007年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(学術雑誌)

    This paper describes a view planning of multiple cameras for tracking multiple persons. View planning of cameras is a very important problem in watching multiple persons in a wide area by using a few cameras. We select fixation points of cameras so that the expected number of tracked persons is maxmized, based on a probabilistic model of person motion. We propose a multi-start local search-based method for tracking persons intermittently using a criterion which allows frequent shifts of fixation points. This view planning outperforms the others and is considered to be appropriate for wide area surveillance systems. We then modify the method so that the planning cost is reduced. We divide the cameras into mutually independent groups based on relations between their veiwing directions and determine fixation points within each group. The performance of this modified method is comparable to the original one with a lower planning cost.

    DOI: 10.7210/jrsj.25.1226

    CiNii Article

    CiNii Research

  • 2A1-C17 複数人物の追跡のための複数カメラの視線プランニング

    武村 紀子, 先山 卓朗, 三浦 純

    ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人 日本機械学会 )   2006 ( 0 )   _2A1-C17_1 - _2A1-C17_4   2006年01月

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    担当区分:筆頭著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)

    This paper describes a view planning of multiple cameras for tracking multiple persons. View planning of cameras is a very important problem in watching multiple persons in a large room by using a few cameras. We select the focuses of attention (FOAs) of cameras efficiently by predicting persons' future positions with their uncertainty. First, we propose an exhaustive search-based planning method and a multi-start local search-based method for tracking persons continuously and compare them. In these methods, we set the FOAs of cameras on the positions so that cameras can catch as many persons as possible. Next, we propose a multi-start local search method for tracking persons intermittently and compare this view planning with others based on a differnt evaluation criterion which allows frequent shifts of the FOAs of cameras. This view planning outperforms the others and is considered to be appropriate for wide area surveillance systems.

    DOI: 10.1299/jsmermd.2006._2a1-c17_1

    CiNii Article

    CiNii Research

    その他リンク: https://www.jstage.jst.go.jp/article/jsmermd/2006/0/2006__2A1-C17_1/_pdf

▼全件表示

著書

  • Handbook of Ambient Intelligence and Smart Environments

    Noriko Takemura, Hiroshi Ishiguro,(Eds. Hideyuki Nakashima, Hami Aghajan, Juan Carlos August)(分担執筆 ,  範囲: Multi-Camera Vision for Surveillance)

    Springer  2010年01月  ( ISBN:978-0-387-93807-3

     詳細を見る

    総ページ数:1294   担当ページ:149-169   記述言語:英語

    DOI: 10.1007/978-0-387-93808-0

口頭発表・ポスター発表等

  • Person segmentation and identification across multiple wearable cameras

    Noriko Takemura, Haruya Sakashita, Shizuka Shirai, Mehrasa Alizadeh, Hajime Nagahara

    International Conference on Quality Control by Artificial Vision 

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    開催期間: 2023年06月   記述言語:英語  

  • A Japanese Dataset for Subjective and Objective Sentiment Polarity Classification in Micro Blog Domain

    Haruya Suzuki, Yuto Miyauchi, Kazuki Akiyama, Tomoyuki Kajiwara, Takashi Ninomiya, Noriko Takemura, Yuta Nakashima, Hajime Nagahara

    Conference on Language Resources and Evaluation 

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    開催期間: 2022年06月   記述言語:英語  

  • 書き手の性格情報を用いた感情強度推定

    鈴木陽也,秋山和輝,梶原智之,二宮崇,武村紀子,中島悠太,長原一

    人工知能学会第36回全国大会 

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    開催期間: 2022年04月   記述言語:日本語  

  • Design of Open-Source Video Viewing Behavior Analysis System,

    Shizuka Shirai, Masumi Hori, Masako Furukawa, Mehrasa Alizadeh, Noriko Takemura, Haruo Takemura, Hajime Nagahara

    International Learning Analytics and Knowledge Conference 

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    開催期間: 2022年03月   記述言語:英語  

  • 深層学習を用いた国際リニアコライダーにおけるフレーバー識別アルゴリズムの開発

    尾上友紀,川越清以,久原真美,末原大幹,津村周作,吉岡瑞樹,長原一,中島悠太,武村紀子

    日本物理学会第77回年次大会 

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    開催期間: 2022年03月   記述言語:日本語  

  • 機械学習を用いたスパースサンプリングによるデータ処理技術の基礎開発

    加藤睦代,岩崎昌子,長原 一,末原大幹,山田悟,中島悠太,武村紀子,中野貴志

    日本物理学会第77回年次大会 

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    開催期間: 2022年03月   記述言語:日本語  

  • リカレントニューラルネットワークを用いた不安状態判別評価

    山本祐輔,田中さや,原地絢斗,村松歩,長原一,武村紀子,水野(松本)由子,下條真司

    第17回日本感性工学会春季大会 

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    開催期間: 2022年03月   記述言語:日本語  

  • 主観と客観の感情極性分類のための日本語データセット

    宮内裕人,鈴木陽也,秋山和輝,梶原智之,二宮崇,武村紀子,中島悠太,長原一

    言語処理学会第28回年次大会 

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    開催期間: 2022年03月   記述言語:日本語  

  • 脳波と心電図を用いたリカレントニューラルネットワークによる快・不快情動の判別評価

    山本祐輔,村松歩,原地絢斗,長原一,武村紀子,中島悠太,水野(松本)由子,下條真司

    日本臨床神経生理学会学術大会 

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    開催期間: 2021年12月   記述言語:日本語  

  • 情動視聴覚刺激後の脳波における回帰分析を用いた時系列変化

    田中さや, 村松歩, 山本祐輔, 原地絢斗, 長原一, 武村紀子, 中島悠太, 水野(松本)由子, 下條真司

    日本臨床神経生理学会学術大会 

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    開催期間: 2021年12月   記述言語:日本語  

  • R&D of the KEK Linac Accelerator Tuning using Machine Learning

    Akihiro Hisano, Masako Iwasaki, Itsuka Satake, Masanori Sato, Hajime Nagahara, Yuta Nakashima, Noriko Takemura, Takashi Nakano

    International Conference on Accelerator and Large Experimental Physics Control Systems 

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    開催期間: 2021年10月   記述言語:英語  

  • 視線情報に基づくVR空間でのマンガ教材読書時の主観的難易度推定

    坂本賢哉,白井詩沙香,武村紀子,Orlosky Jason,長瀧寛之,上田真由美,浦西友樹,竹村治雄

    第64回複合現実感研究会 

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    開催期間: 2021年10月   記述言語:日本語  

  • Learners' efficiency prediction using facial behavior analysis

    Manisha Verma, Yuta Nakashima, Hirokazu Kobori, Ryota Takaoka, Noriko Takemura, Tsukasa Kimura, Hajime Nagahara, Masayuki Numao, Kazumitsu Shinohara

    IEEE International Conference on Image Processing 

     詳細を見る

    開催期間: 2021年09月   記述言語:英語  

  • 機械学習を適用したKEK電子陽電子入射器ビーム調整の開発:加速器シミュレータの基礎開発

    久野彰浩, 岩崎昌子, 佐藤政則, 佐武いつか, 中島悠太, 武村紀子, 長原一, 中野貴志

    日本物理学会2021年秋季大会 

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    開催期間: 2021年09月   記述言語:日本語  

  • 機械学習を適用したKEK電子陽電子入射器ビーム調整システムの開発

    久野彰浩, 岩崎昌子, 佐藤政則, 佐武いつか, 中島悠太, 武村紀子, 長原一, 中野貴志

    第18回日本加速器学会年会 

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    開催期間: 2021年08月   記述言語:日本語  

  • WRIME: A New Dataset for Emotional Intensity Estimation with Subjective and Objective Annotations,

    Tomoyuki Kajiwara, Chenhui Chu, Noriko Takemura, Yuta Nakashima, Hajime Nagahara

    2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics 

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    開催期間: 2021年07月   記述言語:英語  

  • グラフ畳み込みネットワークを用いたグループ学習時の活性度推定

    福井嵐志,武村紀子,白井詩沙香,Mehrasa Alizadeh,長原一

    画像の認識・理解シンポジウム 

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    開催期間: 2021年07月   記述言語:日本語  

  • 素粒子物理学実験への機械学習の適用研究

    岩崎昌子,久野彰浩,加藤睦代,末原大幹,山田悟,長原一,中島悠太,武村紀子,中野貴志

    学際大規模情報基盤共同利用・共同研究拠点(JHPCN) 第13回シンポジウム 

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    開催期間: 2021年07月   記述言語:日本語  

  • 強化学習を用いたKEK Linac加速器運転調整システムの開発

    久野彰浩, 岩崎昌子,佐藤政則,佐武いつか,中島悠太,武村紀子,長原一,中野貴志

    日本物理学会第76回年次大会 

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    開催期間: 2021年03月   記述言語:日本語  

  • 主観感情と客観感情の強度推定のための日本語データセット

    梶原智之, Chenhui Chu, 武村紀子, 中島悠太, 長原一

    言語処理学会第27回年次大会 

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    開催期間: 2021年03月   記述言語:日本語  

  • 複数ウェアラブルカメラ映像の人物識別とセグメンテーション

    坂下晴哉,武村紀子,白井詩沙香,Alizadeh Mehrasa,長原一

    情報処理学会コンピュータビジョンとイメージメディア研究会1月研究会 

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    開催期間: 2021年01月   記述言語:日本語  

  • Public Meeting Corpus Construction and Information Extraction

    Chenhui Chu, Felix Giovanni Virgo, Koji Tanaka, Takaya Ogawa, Kazuki Ashihara, Tomoyuki Kajiwara, Yuta Nakashima, Noriko Takemura, Hajime Nagahara, Takao Fujikawa

    第70回日本西洋史学会大会 

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    開催期間: 2020年12月   記述言語:英語  

  • IDSOU at WNUT-2020 Task2: Identification of Informative COVID-19 English Tweets

    Sora Ohashi, Tomoyuki Kajiwara, Chenhui Chu, Noriko Takemura, Yuta Nakashima, Hajime Nagahara

    Workshop on Noisy User-generated Text 

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    開催期間: 2020年11月   記述言語:英語  

  • 視聴覚刺激後の脳波を用いたニューラルネットワークによる情動判別評価

    山本 祐輔, 村松 歩, 長原 一, 武村 紀子, 中島 悠太, 水野(松本)由子, 下條真司

    日本臨床神経生理学会学術大会 

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    開催期間: 2020年11月   記述言語:日本語  

  • スマートフォンを用いた情動刺激時における脳波の次数中心性

    村松歩、山本祐輔、長原一、武村紀子、中島悠太、水野(松本)由子、下條真司

    日本臨床神経生理学会学術大会 

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    開催期間: 2020年11月   記述言語:日本語  

  • ニューラルネットワークを使用した脈波解析による恐怖状態の判別手法の開発

    原地 絢斗,山本 祐輔,村松 歩,長原 一,武村 紀子,中島 悠太,水野(松本)由子,下條 真司

    日本臨床神経生理学会学術大会 

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    開催期間: 2020年11月   記述言語:日本語  

  • 脳波を用いた機械学習による怒り情動検知システムの構築

    田村高基, 山本祐輔, 村松歩, 長原一, 武村紀子, 中島悠太, 水野(松本)由子, 下條真司

    日本臨床神経生理学会学術大会 

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    開催期間: 2020年11月   記述言語:日本語  

  • Estimation of Wakefulness in Video-based Lectures based on Multimodal Data Fusion

    Ryosuke Kawamura, Shizuka Shirai, Mehrasa Alizadeh, Noriko Takemura, Hajime Nagahara

    ACM International Joint Conference on Pervasive and Ubiquitous Computing / ACM International Symposium on Wearable Computers 

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    開催期間: 2020年09月   記述言語:英語  

  • 機械学習を用いたILC SiD測定器電磁カロリメータエネルギー較正の開発(3)

    中祐介, 岩崎昌子, J. Barkeloo, J. Brau, L. Braun, C. Potter, A. Steinhebel, J. Strube, M. Breidenbach, 武村紀子, 中島悠太, 長原一

    日本物理学会2020年秋季大会 

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    開催期間: 2020年09月   記述言語:日本語  

  • 深層学習を用いたILD崩壊点検出アルゴリズムの改良

    後藤輝一, 末原大幹, 川越清以, 吉岡瑞樹, 倉田正和, 長原一, 中島悠太, 武村紀子

    日本物理学会2020年秋季大会 

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    開催期間: 2020年09月   記述言語:日本語  

  • 強化学習を用いた KEK Linac 加速器運転調整のための準備研究

    久野彰浩, 岩崎昌子,佐藤政則,佐武いつか,中島悠太,武村紀子,長原一,中野貴志

    日本加速器学会年会 

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    開催期間: 2020年09月   記述言語:日本語  

  • How Confident Are You in Your Estimate of Human Age? Uncertainty-aware Gait -based Age Estimation by Label Distribution Learning

    Atsuya Sakata, Yasushi Makihara, Noriko Takemura, Daigo Muramatsu, Yasushi Yagi

    4th Int. Joint Conference on Biometrics, 2020 

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    開催期間: 2020年09月   記述言語:英語  

  • Heat environment increases mental workload even if learning efficiency is enhanced

    Tsukasa Kimura, Noriko Takemura, Yuta Nakashima, Hirokazu Kobori, Hajime Nagahara, Masayuki Numao, Kazumitsu Shinohara

    27th Annual Meeting of the Cognitive Neuroscience Society 

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    開催期間: 2020年05月   記述言語:英語  

  • Constructing a Public Meeting Corpus

    Chenhui Chu, Koji Tanaka, Haolin Ren, Benjamin Renoust, Yuta Nakashima, Noriko Takemura, Hajime Nagahara, Takao Fujikawa

    Language Resources and Evaluation Conference 

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    開催期間: 2020年05月   記述言語:英語  

  • Toward Predicting Learners’ Efficiency for Adaptive e-Learning

    Yuta Nakashima, Hirokazu Kobori, Ryota Takaoka, Noriko Takemura, Tsukasa Kimura, Hajime Nagahara, Masayuki Numao, Kazumitsu Shinohara

    International Conference on Learning Analytics & Knowledge 

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    開催期間: 2020年03月   記述言語:英語  

  • A Survey of Learners’ Video Watching Behavior in Blended Learning

    Mehrasa Alizadeh, Shizuka Shirai, Noriko Takemura, Shogo Terai, Yuta Nakashima, Hajime Nagahara, Haruo Takemura

    Workshop on Addressing Drop-Out Rates in Higher Education 

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    開催期間: 2020年03月   記述言語:英語  

  • Detecting Learner Drowsiness Based on Facial Expressions and Head Movements in Online Courses

    Shogo Terai, Shizuka Shirai, Mehrasa Alizadeh, Ryosuke Kawamura, Noriko Takemura, Yuki Uranishi, Haruo Takemura, Hajime Nagahara

    ACM International Conference on Intelligent User Interfaces Companion 

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    開催期間: 2020年03月   記述言語:英語  

  • Exploring Pupillometry as a Method to Evaluate Reading Comprehension in VR-based Educational Comics

    Kenya Sakamoto, Shizuka Shirai, Jason Orlosky, Hiroyuki Nagataki, Noriko Takemura, Mehrasa Alizadeh, Mayumi Ueda

    IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops 

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    開催期間: 2020年03月   記述言語:英語  

  • Legal Information as a Complex Network: Improving Topic Modeling through Homophily

    Kazuki Ashihara, Chenhui Chu, Benjamin Renoust, Noriko Okubo, Noriko Takemura, Yuta Nakashima, Hajime Nagahara

    International Conference on Complex Networks and their Applications 

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    開催期間: 2019年12月   記述言語:英語  

  • 追加ラベルを組み込んだ歩容特徴抽出器

    守脇幸佑,村松大吾,武村紀子,八木康史,“追加ラベルを組み込んだ歩容特徴抽出器”

    第9回バイオメトリクスと認識・認証シンポジウム 

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    開催期間: 2019年12月   記述言語:日本語  

  • Public Meeting Corpus Construction and Content Delivery

    Chenhui Chu, Koji Takanka, Haolin Ren, Benjamin Renoust, Yuta Nakashima, Noriko Takemura, Hajime Nagahara, Takao Fujikawa

    人文科学とコンピュータシンポジウム 

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    開催期間: 2019年12月   記述言語:英語  

  • R&D of the Energy Calibration for the SiD EM Calorimeter based on Machine Learning

    Masako Iwasaki, Yusuke Naka, Jim Brau, Martin Breidenbach, Koki Morikawa, Hajime Nagahara, Yuta Nakashima, Amanda Lynn Steinhebel, Jan Fridolf Strube, Noriko Takemura

    The third edition of the Calorimetry for High Energy Frontier Conference 

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    開催期間: 2019年11月   記述言語:英語  

  • R&D of the Flavor-tag Method based on Machine Learning for High Energy Experiments

    Naoya Kishida, Masako Iwasaki, Yuta Nakashima, Noriko Takemura, Hajime Nagahara, Takashi Nakano

    International Workshop on Future Linear Colliders 

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    開催期間: 2019年10月   記述言語:英語  

  • 追加ラベルを組み込んだ歩容特徴抽出器

    守脇幸佑,村松大吾,武村紀子,八木康史

    バイオメトリクス研究会 

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    開催期間: 2019年10月   記述言語:日本語  

  • Facial Expression Recognition with Skip-connection to Leverage Low-level Features”

    Manisha Verma, Hirokazu Kobori, Yuta Nakashima, Noriko Takemura, Hajime Nagahara

    IEEE International Conference on Image Processing 

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    開催期間: 2019年09月   記述言語:英語  

  • 歩行映像解析による体組成推定に関する一検討

    廖若辰, 守脇幸佑, 槇原靖, 村松大吾, 武村紀子, 八木康史

    情報処理学会研究報告コンピュータビジョンとイメージメディア 

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    開催期間: 2019年09月   記述言語:日本語  

  • Belle実験におけるB0→γγ崩壊過程の研究-機械学習を用いた新しい解析手法の開発-

    岸田 直也, 岩崎 昌子, 石川 明正, 中島 悠太, 武村 紀子, 長原 一, 中野 貴志, 他BelleCollab., RCNP深層学習プロジェクトグループ

    日本物理学会2019年秋季大会 

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    開催期間: 2019年09月   記述言語:日本語  

  • 機械学習を使用したKEK Linac加速器運転調整システムの開発

    城庵 颯, 岩崎 昌子, 佐藤 政則, 佐武 いつか, 中島 悠太, 武村 紀子, 長原 一, 中野貴志

    日本物理学会2019年秋季大会 

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    開催期間: 2019年09月   記述言語:日本語  

  • 温熱環境・学習効率・精神負荷の関係

    木村司,武村紀子,中島悠太,小堀寛和,長原一,沼尾正行,篠原一光

    ヒューマンインタフェースシンポジウム 

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    開催期間: 2019年09月   記述言語:日本語  

  • 機械学習を使用したKEK Linac加速器運転調整システムの開発

    城庵 颯, 岩崎 昌子, 佐藤 政則, 佐武 いつか, 中島 悠太, 武村 紀子, 長原 一, 中野貴志

    第16回日本加速器学会年会 

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    開催期間: 2019年07月   記述言語:日本語  

  • 歩容による疲労判定に向けて:データ収集と基礎解析

    西川博文,青木工太,村松大吾,槇原靖,武村紀子,八木康史

    第22回画像の認識・理解シンポジウム 

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    開催期間: 2019年07月   記述言語:日本語  

  • Incorporation of extra pseudo labels for CNN-based gait recognition

    Kosuke Moriwaki, Daigo Muramatsu, Noriko Takemura, Yasushi Yagi

    第22回画像の認識・理解シンポジウム 

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    開催期間: 2019年07月   記述言語:日本語  

  • Pseudo normal image generation for anomaly detection on road surface,

    Naoyuki Mori, Noriko Takemura, Yasushi Yagi

    International Conference on Quality Control by Artificial Vision 

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    開催期間: 2019年05月   記述言語:英語  

  • Multimodal learning analytics: Society 5.0 project in Japan

    Shizuka Shirai, Noriko Takemura, Yuta Nakashima, Hajime Nagahara, and Haruo Takemura

    Int. Conf. Learning Analytics and Knowledge 

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    開催期間: 2019年03月   記述言語:英語  

  • 歴史新聞データからのコーパス構築

    田中昂志,Chenhui Chu,中島悠太,武村紀子,長原一,藤川隆男

    言語処理学会 第25回年次大会 

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    開催期間: 2019年03月   記述言語:日本語  

  • 機械学習を用いたフレーバ識別用ツールの開発

    岸田直也,岩崎昌子,中島悠太,武村紀子,長原一,中野貴志

    日本物理学会第74回年次大会 

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    開催期間: 2019年03月   記述言語:日本語  

  • R&D of the Flavor-tag Method based on Machine Learning for High Energy Experiments

    Naoya Kishida, Masako Iwasaki, Yuta Nakashima, Noriko Takemura, Takashi Nakano

    The 2nd KMI school 

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    開催期間: 2019年02月   記述言語:英語  

  • Gait-based Age Estimation using a DenseNet

    Atsuya Sakata, Yasushi Makihara, Noriko Takemura, Daigo Muramatsu, Yasushi Yagi

    International Workshop on Robust Computer Vision 

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    開催期間: 2019年01月   記述言語:英語  

  • Multi-view large population gait dataset and its performance evaluation for cross-view gait recognition

    Noriko Takemura, Yasushi Makihara, Daigo Muramatsu, Tomio Echigo, Yasushi Yagi

    International Workshop on Robust Computer Vision 

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    開催期間: 2019年01月   記述言語:英語  

  • The OU-ISIR Large Population Gait Database with Real-Life Carried Object and its performance evaluation

    Md. Zasim Uddin, Trung Thanh Ngo, Yasushi Makihara, Noriko Takemura, Xu Li, Daigo Muramatsu, Yasushi Yagi

    International Workshop on Robust Computer Vision 

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    開催期間: 2019年01月   記述言語:英語  

  • Gait-based Age Estimation using a DenseNet

    Atsuya Sakata, Yasushi Makihara, Noriko Takemura, Daigo Muramatsu, Yasushi Yagi

    International Workshop on Attention/Intention Understanding 

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    開催期間: 2018年12月   記述言語:英語  

  • CNNに基づいた歩容クラス識別における中間出力の個人性評価

    守脇幸佑,村松大吾,武村紀子,八木康史

    第8回バイオメトリクスと認識・認証シンポジウム 

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    開催期間: 2018年11月   記述言語:日本語  

  • 歩容による推定年齢と健康年齢に関する考察

    阪田篤哉,西川博文,武村紀子,槇原康史,村松大吾,八木康史

    第8回バイオメトリクスと認識・認証シンポジウム 

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    開催期間: 2018年11月   記述言語:日本語  

  • 歩容による推定年齢と健康年齢に関する考察

    阪田篤哉,西川博文,武村紀子,槇原康史,村松大吾,八木康史

    電子情報通信学会バイオメトリクス10月研究会 

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    開催期間: 2018年10月   記述言語:日本語  

  • CNNの基づいた歩容クラス識別における中間出力の個人性評価

    守脇幸佑,村松大吾,武村紀子,八木康史

    電子情報通信学会バイオメトリクス10月研究会 

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    開催期間: 2018年10月   記述言語:日本語  

  • Convolutional Neural Network-based Road Damage Detection

    森直幸,武村紀子,八木康史

    第21回画像の認識・理解シンポジウム 

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    開催期間: 2018年08月   記述言語:日本語  

  • Gait-based Age Estimation via Multi-Stage Convolutional Neural Network

    Atsuya Sakata, Noriko Takemura, Yasushi Yagi,

    第21回画像の認識・理解シンポジウム 

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    開催期間: 2018年08月   記述言語:日本語  

  • 多段階畳み込みニューラルネットワークを用いた歩容に基づく年齢推定

    阪田篤哉,武村紀子,八木康史

    情報処理学会研究報告コンピュータビジョンとイメージメディア 

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    開催期間: 2018年05月   記述言語:日本語  

  • Appropriate Network Architecture According to a Situation for Convolutional Neural Network-based Cross-view Gait Recognition

    Noriko Takemura, Yasushi Makihara, Daigo Muramatsu, Tomio Echigo, Yasushi Yagi

    International Workshop on Robust Computer Vision 

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    開催期間: 2018年01月   記述言語:英語  

  • CNNを用いた視点変化に頑健な歩容認証における入出力構造の一検討

    武村紀子,槇原靖,村松大吾,越後富夫,八木康史

    情報処理学会研究報告コンピュータビジョンとイメージメディア 

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    開催期間: 2017年11月   記述言語:日本語  

  • 照明環境に対する快不快推定のための能動的アンビエントセンシング

    菊川剛,武村紀子,佐藤宏介

    第22回日本顔学会大会(フォーラム顔学2017) 

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    開催期間: 2017年09月   記述言語:日本語  

  • Convolutional Neural Networkを用いた道路舗装表面の異常検出

    森直幸,武村紀子,八木康史

    第20回画像の認識・理解シンポジウム 

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    開催期間: 2017年08月   記述言語:日本語  

  • 多視点大規模歩容データベースの構築と異なる視点における歩容認証の性能評価

    武村紀子,槇原靖,村松大吾,越後富夫,八木康史

    電子情報通信学会バイオメトリクス3月研究会 

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    開催期間: 2017年03月   記述言語:日本語  

  • Mental Fatigue Estimation Based on Luminance Change of Facial Image

    Ryosuke Kawamura, Noriko Takemura, Kosuke Sato

    International Symposium on System Integration 

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    開催期間: 2016年12月   記述言語:英語  

  • 畳み込みニューラルネットワークを用いた視点変化に頑健な歩容認証 招待有り

    武村紀子,白神康平,槇原靖,村松大吾,越後富夫,八木康史

    第6回バイオメトリクスと認識・認証シンポジウム 

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    開催期間: 2016年11月   記述言語:日本語  

  • 照明変動に起因する無意識的行動に基づく快不快推定

    菊川剛,武村紀子,佐藤宏介

    第60回システム制御情報学会研究発表講演会 

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    開催期間: 2016年05月   記述言語:日本語  

  • Mental Fatigue Estimation based on Facial Expressions During Speech

    Ryosuke Kawamura, Noriko Takemura, Kosuke Sato

    International Symposium on System Integration 

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    開催期間: 2015年12月   記述言語:英語  

  • Evaluation and Fair Comparison of Human Tracking Methods with PTZ Cameras

    Alparslan Yildiz, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    HCI International 

     詳細を見る

    開催期間: 2015年08月   記述言語:英語  

  • 発話時の表情変化に基づく疲労推定

    川村亮介,武村紀子,佐藤宏介

    第59回システム制御情報学会研究発表講演会 

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    開催期間: 2015年05月   記述言語:日本語  

  • An input-assist system considering non-periodic involuntary hand movements

    Kai Wang, Sei Ikeda, Noriko Takemura, Daisuke Iwai, Kosuke Sato

    第59回システム制御情報学会研究発表講演会 

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    開催期間: 2015年05月   記述言語:英語  

  • An Input-Assist System for Hand Tremor

    Kai Wang, Sei Ikeda, Noriko Takemura, Daisuke Iwai, Kosuke Sato

    Korea-Japan Workshop on Mixed Reality 

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    開催期間: 2015年04月   記述言語:英語  

  • Multi-sensor-based Ambient Sensing System for the Estimation of Comfort/Discomfort During Desk Work

    Kengo Yoshimizu, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    International Symposium on System Integration 

     詳細を見る

    開催期間: 2014年12月   記述言語:英語  

  • Building Evaluation Databases for Comparative Analysis of Active Camera Tracking Methods

    Alparslan Yildiz,武村紀子,岩井儀雄,佐藤宏介

    第17回画像の認識・理解シンポジウム 

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    開催期間: 2014年07月   記述言語:英語  

  • ProCams-Based Cybernetics: プロジェクタカメラ系による身体と環境のサイバー拡張

    佐藤宏介,岩井大輔,池田聖,武村紀子

    日本バーチャルリアリティ学会 複合現実感研究会 

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    開催期間: 2014年01月   記述言語:日本語  

  • Regression Based Trajectory Learning & Prediction for Human Motion

    Alparslan Yildiz, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    Workshop on Geometric Computation for Computer Vision 

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    開催期間: 2013年10月   記述言語:英語  

  • Tracking People with Active Cameras

    Alparslan Yildiz, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    HCI International 

     詳細を見る

    開催期間: 2013年07月   記述言語:英語  

  • 快適な照明環境構築のための距離特徴量を用いた無意識的表情変化の自動検出

    北村謙典,武村紀子,岩井儀雄,佐藤宏介

    第15回 画像の認識・理解シンポジウム 

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    開催期間: 2012年08月   記述言語:日本語  

  • 占有マップを用いた複数アクティブカメラによる人物追跡

    Alparslan Yildiz,武村紀子,岩井儀雄,佐藤宏介

    第15回 画像の認識・理解シンポジウム 

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    開催期間: 2012年08月   記述言語:日本語  

  • Automatic Detection of Unconscious Reactions to Illuminance Change in Illumination

    Kensuke Kitamura, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    VII Conference on Articulated Motion and Deformable Objects 

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    開催期間: 2012年07月   記述言語:英語  

  • 発話履歴を利用した対話相手の意図推定

    曽根孝基,武村紀子,中村泰,吉川雄一郎,石黒浩

    ロボティクス・メカトロニクス講演会 

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    開催期間: 2012年05月   記述言語:日本語  

  • 対人インタラクションアバタの作成に必要な再生技術の検討

    原健太,武村紀子,岩井儀雄,佐藤宏介

    電子情報通信学会技術研究報告 

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    開催期間: 2012年01月   記述言語:日本語  

  • 照度変動に対する無意識下での表出行動検出

    北村謙典,武村紀子,岩井儀雄,佐藤宏介

    情報処理学会 コンピュータビジョンとイメージメディア研究会 

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    開催期間: 2012年01月   記述言語:日本語  

  • A Tabletop Interface Using Nail Images and Real Object Recognition

    Kenta Hara, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    International Joint Conference on Ambient Intelligence 

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    開催期間: 2011年11月   記述言語:英語  

  • Extracting Interval Distribution of Human Interaction

    Ryohei Kimura, Noriko Takemura, Yoshio Iwai, Kosuke Sato

    Pacific-Rim Symposium on Image and Video Technology 

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    開催期間: 2011年11月   記述言語:英語  

  • 生体ゆらぎ理論に基づく室内照明の適応的制御

    松本裕樹,武村紀子,中村泰,岩井儀雄,石黒浩

    計測自動制御学会システム・情報部門学術講演会 

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    開催期間: 2011年11月   記述言語:日本語  

  • A Path Planning Method for Human Tracking Agents Using Variable-term Prediction based on Dynamic k-Nearest Neighbor Algorithm

    Noriko Takemura, Yutaka Nakamura, Hiroshi Ishiguro

    International Conference on Intelligent Robots and Systems  

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    開催期間: 2011年09月   記述言語:英語  

  • エージェント対話システムにおける仮説に基づくエージェント発話計画

    曽根孝基,武村紀子,中村泰,石黒浩

    ロボット学会学術講演会 

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    開催期間: 2011年09月   記述言語:日本語  

  • マルチモーダル情報を用いた人物対話行動における応答時間分布抽出

    木村綾平,武村紀子,岩井儀雄,佐藤宏介

    ロボット学会学術講演会 

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    開催期間: 2011年09月   記述言語:日本語  

  • 人物対話行動における応答時間分布抽出

    木村綾平,武村紀子,岩井儀雄,佐藤宏介

    第14回 画像の認識・理解シンポジウム 

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    開催期間: 2011年07月   記述言語:日本語  

  • 快適な光環境構築のための表出行動抽出

    北村謙典,武村紀子,岩井儀雄,佐藤宏介

    第14回 画像の認識・理解シンポジウム 

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    開催期間: 2011年07月   記述言語:日本語  

  • 可変長予測に基づいた人物追跡のための複数エージェントの経路計画法

    武村紀子,中村泰,石黒浩

    ロボティクスシンポジア 

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    開催期間: 2011年03月   記述言語:日本語  

  • A Path Planning Method for Human Tracking Agents using Variable-term Prediction

    Noriko Takemura, Yutaka Nakamura, Yoshio Matsumoto, Hiroshi Ishiguro

    International Conference on Artificial Neural Networks 

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    開催期間: 2010年09月   記述言語:英語  

  • 長期予測に基づいた人物追跡のための複数エージェントの経路計画法

    武村紀子,中村泰,松本吉央,石黒浩

    ロボティクス・メカトロニクス講演会 

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    開催期間: 2010年06月   記述言語:日本語  

  • Human Tracking with Variable Prediction Steps based on Kullback-Leibler Divergence

    Noriko Takemura, Yutaka Nakamura, Yoshio Matsumoto, Hiroshi Ishiguro

    International Symposium on Artificial Life and Robotics 

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    開催期間: 2010年02月   記述言語:英語  

  • 可変長予測に基づく人物追跡

    武村紀子,中村泰,松本吉央,石黒浩

    情報処理学会関西支部支部大会 

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    開催期間: 2009年09月   記述言語:日本語  

  • 広域監視のための複数エージェントの経路計画

    武村紀子,中村泰,小泉智史,松本吉央,石黒浩

    ロボティクス・メカトロニクス講演会 

     詳細を見る

    開催期間: 2009年05月   記述言語:日本語  

  • 複数人物追跡のための複数カメラの注視点選択

    武村紀子,三浦純,石黒浩

    ロボティクス・メカトロニクス講演会 

     詳細を見る

    開催期間: 2008年06月   記述言語:日本語  

  • 複数カメラ視線プランニング問題の2段階解法

    武村紀子,三浦純,石黒浩

    ロボティクスシンポジア 

     詳細を見る

    開催期間: 2008年03月   記述言語:日本語  

  • View Planning of Multiple Active Cameras for Wide Area Surveillance

    Noriko Takemura, Jun Miura

    International Conference on Robotics and Automation 

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    開催期間: 2007年04月   記述言語:英語  

  • 多スタート局所探索法を用いた複数人物追跡のための複数能動カメラの同時視線プランニング

    武村紀子,三浦純

    ロボット学会学術講演会 

     詳細を見る

    開催期間: 2006年09月   記述言語:日本語  

  • View Planning Algorithms for a Multi-camera Surveillance System

    Jun Miura, Noriko Takemura, Takuro Sakiyama

    ICAPS-2006 workshop on planning under Uncertainty and Execution Control for Autonomous Systems 

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    開催期間: 2006年06月   記述言語:英語  

  • 複数人物の追跡のための複数カメラの視線プランニング

    武村紀子,先山卓朗,三浦純

    ロボティクス・メカトロニクス講演会 

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    開催期間: 2006年05月   記述言語:日本語  

  • 顔画像を用いた個人特徴の減算によるユーザの曖昧な内部状態推定

    朝枝彩夏, 武村紀子

    情報科学技術フォーラム 

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    開催期間: 2023年09月   記述言語:日本語  

  • 機械学習を用いた加速器調整システムの開発: GANを用いた加速器シミュレータの開発

    度会龍, 岩崎昌子, 中島悠太, 武村紀子, 長原一, 中野貴志, 佐藤政則, 佐武いつか

    第20回日本加速器学会年会 

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    開催期間: 2023年09月   記述言語:日本語  

  • 座圧分布の時系列変化に基づく協調学習における話者推定

    江角翼, 武村紀子

    情報科学技術フォーラム 

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    開催期間: 2023年09月   記述言語:日本語  

  • 変分オートエンコーダを用いた個人特徴の分離による歩容映像に基づく疾患推定

    古川栞, 武村紀子

    情報科学技術フォーラム 

     詳細を見る

    開催期間: 2023年09月   記述言語:日本語  

  • 座圧情報を用いたグループ活動における話者推定

    江角翼, 武村紀子

    画像の認識・理解シンポジウム 

     詳細を見る

    開催期間: 2023年07月   記述言語:日本語  

  • 顔画像における個人特徴の分離による個人差を考慮したユーザ状態推定

    朝枝彩夏, 武村紀子

    画像の認識・理解シンポジウム 

     詳細を見る

    開催期間: 2023年07月   記述言語:日本語  

  • 変分オートエンコーダを用いた歩容映像の個人特徴を考慮した疾患推定

    古川栞, 武村紀子

    画像の認識・理解シンポジウム 

     詳細を見る

    開催期間: 2023年07月   記述言語:日本語  

  • ILCのためのグラフニューラルネットワークを用いたフレーバー識別アルゴリズムの開発

    尾上友紀, 末原大幹, 川越清以, 吉岡瑞樹, 中島悠太, 長原一, 武村紀子

    日本物理学会 2023年春季大会 

     詳細を見る

    開催期間: 2023年03月   記述言語:日本語  

  • GANを用いた加速器シミュレータの開発

    度会龍, 岩崎昌子, 中島悠太, 武村紀子, 長原一, 中野貴志, 佐藤政則, 佐武いつか

    日本物理学会 2023年春季大会 

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    開催期間: 2023年03月   記述言語:日本語  

  • ILCのためのグラフニューラルネットワークを用いたカロリメータークラスタリング手法の開発

    津村周作, 末原大幹, 川越清以, 吉岡瑞樹, 長原一, 中島悠太, 武村紀子

    日本物理学会 2023年春季大会 

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    開催期間: 2023年03月   記述言語:日本語  

  • Society5.0における未来の支援システム

    武村紀子

    産学協力研究コンソーシアム インターネット技術研究会(ITRC)第52回研究会(meet52 

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    開催期間: 2022年11月   記述言語:日本語  

  • カオス理論に基づく情動刺激時における脳波のリアプノフ指数

    村松歩, 山本祐輔, 原地絢斗, 長原一, 武村紀子, 水野(松本)由子, 下條真司

    第52回日本臨床神経生理学会学術大会 

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    開催期間: 2022年11月   記述言語:日本語  

  • 心電図を用いた情動視聴覚刺激が及ぼす不安状態の違いによる心拍変動解析

    田邉晃史, 山本祐輔, 原地絢斗, 村松歩, 長原一, 武村紀子, 水野(松本)由子, 下條真司

    第52回日本臨床神経生理学会学術大会 

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    開催期間: 2022年11月   記述言語:日本語  

  • 脳波と脈波を使用した情動判別のためのMultimodal Recurrent Neural Network の開発

    原地絢斗, 山本祐輔, 村松歩, 長原一, 武村紀子, 水野(松本)由子, 下條真司

    第52回日本臨床神経生理学会学術大会 

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    開催期間: 2022年11月   記述言語:日本語  

  • 不安状態の違いによる情動刺激後における脳波による脳内ネットワークの媒介中心性

    山本祐輔, 村松歩, 原地絢斗, 長原一, 武村紀子, 水野(松本)由子, 下條真司

    第52回日本臨床神経生理学会学術大会 

     詳細を見る

    開催期間: 2022年11月   記述言語:日本語  

  • Recurrent Neural Network によるてんかん性異常波と健常脳波の判別

    砥山峻太郎, 村松歩, 原地絢斗, 山本祐輔, 長原一, 武村紀子, 水野(松本)由子, 下條真司

    第52回日本臨床神経生理学会学術大会 

     詳細を見る

    開催期間: 2022年11月   記述言語:日本語  

  • 周波数解析とコンターマップを用いた軽度認知症患者の脳波特徴抽出

    橋本賢治, 山本祐輔, 原地絢斗, 村松歩, 水野(松本)由子, 長原一, 武村紀子, 下條真司

    第52回日本臨床神経生理学会学術大会 

     詳細を見る

    開催期間: 2022年11月   記述言語:日本語  

  • Incorporation of Extra Pseudo Labels for CNN-based Gait Recognition

    Daigo Muramatsu, Kosuke Moriwaki, Yoshiki Maruya, Noriko Takemura, Yasushi Yagi

    International Conference of the Biometrics Special Interest Group 

     詳細を見る

    開催期間: 2022年09月   記述言語:英語  

  • 機械学習を用いたスパースサンプリングによるデータ処理技術の基礎開発(II)

    加藤睦代,岩崎昌子,長原一,末原大幹,山田悟,中島悠太,武村紀子,中野貴志

    日本物理学会2022年秋季大会 

     詳細を見る

    開催期間: 2022年09月   記述言語:日本語  

  • 国際リニアコライダー計画における深層学習を用いたシャワークラスタリングアルゴリズムの開発

    津村周作,末原大幹,川越清以,吉岡瑞樹,長原一,中島悠太,武村紀子

    日本物理学会2022年秋季大会 

     詳細を見る

    開催期間: 2022年09月   記述言語:日本語  

  • マンガ教材読書時のリアルタイム難易度推定に向けた視線ヒートマップ分解能の検討

    坂本賢哉,白井詩沙香,武村紀子,Orlosky Jason,長瀧寛之,上田真由美,浦西友樹,竹村治雄

    第27回バーチャルリアリティ学会大会 

     詳細を見る

    開催期間: 2022年09月   記述言語:日本語  

  • Multi-label disengagement and behavior prediction in online learning

    Manisha Verma, Yuta Nakashima, Noriko Takemura, Hajime Nagahara

    International Conference on Artificial Intelligence in Education 

     詳細を見る

    開催期間: 2022年07月   記述言語:英語  

  • 偏りのある学習データ下における要因抑制学習を用いた歩容年齢推定

    山野広大,村松大吾,武村紀子,八木康史

    第25回画像の認識・理解シンポジウム 

     詳細を見る

    開催期間: 2022年07月   記述言語:日本語  

  • 不確かさを考慮した単眼カメラ動画像からの三次元人物姿勢推定

    冨樫睦輝,武村紀子,福井嵐士,大倉史生,長原一

    第25回画像の認識・理解シンポジウム 

     詳細を見る

    開催期間: 2022年07月   記述言語:日本語  

▼全件表示

工業所有権

  • 効率推定装置

     詳細を見る

    出願番号:2021-002281  出願日:2021年01月08日

    公開番号:2021-140139 

  • 空調システム及び空調方法

     詳細を見る

    出願番号:2013-145775  出願日:2013年07月11日

    公開番号:2015-017767 

    登録番号:6259597 

  • 表情検出システム及び表情検出方法

     詳細を見る

    出願番号:2013-112410  出願日:2013年05月28日

    公開番号:2014-232958 

    登録番号:6202882 

  • 照明制御システム及び照明制御方法

     詳細を見る

    出願番号:2012-274169  出願日:2012年12月17日

    公開番号:2014-120304 

    登録番号:6118098 

  • 機械学習プログラム、機械学習方法および機械学習装置

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    出願番号:2022-178823  出願日:2022年11月08日

  • 被験者の状態を推定するためのコンピュータシステム、方法、およびプログラム

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    出願番号:2022-566687  出願日:2022年06月07日

  • 顔しかめ検出システム及び顔しかめ検出方法

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    出願番号:2012-149853  出願日:2012年07月03日

    公開番号:2014-013447 

    登録番号:6075982 

  • 不快度推定システム及び不快度推定方法

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    出願番号:2012-149854  出願日:2012年07月03日

    公開番号:2014-013448 

    登録番号:6075983 

  • 照明制御システム及び照明制御方法

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    出願番号:2012-028423  出願日:2012年02月13日

    公開番号:2013-165031 

    登録番号:5921242 

  • 照明制御システム及び照明制御方法

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    出願番号:2012-002625  出願日:2012年01月10日

    公開番号:2013-143248 

    登録番号:5941284 

▼全件表示

教育活動に関する受賞・指導学生の受賞など

  • FIT奨励賞

    情報処理学会,電子情報通信学会   座圧分布の時系列変化に基づく協調学習における話者推定  

    2023年09月23日

    江角翼(指導学生)

  • FIT奨励賞

    情報処理学会,電子情報通信学会   顔画像を用いた個人特徴の減算によるユーザの曖昧な内部状態推定  

    2023年09月23日

    朝枝彩夏(指導学生)

学会・委員会等活動

  • Asian Conference on Pattern Recognition   Program chair  

    2022年04月 - 現在

  • 阪大病院AIホスピタル 情報活用審査委員会   副委員長  

    2021年04月 - 現在

ベンチャー企業設立

  • 株式会社ayumo

    技術顧問

    2023年06月27日

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    歩行困難に悩む人々が早期に適切な治療が受けられるための支援と,運動機能の改善に貢献