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

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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

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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

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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

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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

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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

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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

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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

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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

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

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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

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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/

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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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）

Dynamic facial expression recognition (DFER) is an important task in the field of computer vision. To apply automatic DFER in practice, it is necessary to accurately recognize ambiguous facial expressions, which often appear in data in the wild. In this paper, we propose MIDAS, a data augmentation method for DFER, which augments ambiguous facial expression data with soft labels consisting of probabilities for multiple emotion classes. In MIDAS, the training data are augmented by convexly combining pairs of video frames and their corresponding emotion class labels, which can also be regarded as an extension of mixup to soft-labeled video data. This simple extension is remarkably effective in DFER with ambiguous facial expression data. To evaluate MIDAS, we conducted experiments on the DFEW dataset. The results demonstrate that the model trained on the data augmented by MIDAS outperforms the existing state-of-the-art method trained on the original dataset.

DOI： 10.1109/WACV57701.2024.00642

Scopus

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担当区分：最終著者,　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）

担当区分：最終著者,　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）

担当区分：最終著者,　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）

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 the intermediate results of our Mixed Reality (MR)-based visualisation prototype for teaching assistants (TAs) to support collaborative learning. Many universities have introduced TA programs; however, it is not easy for TAs to understand students’ engagement states in collaborative learning activities due to their lack of teaching experience. The proposed MR-based visualisation overlays student activity states above each group location to facilitate decision-making for TAs as to whether support is needed or not. To examine the proposed solution’s impact, we conducted an exploratory experiment using a prototype with a Wizard of Oz method. The results indicated that the prototype has the potential to support TAs in noticing groups that need support and increases their efficiency.

DOI： 10.1007/978-3-031-49212-9_42

Scopus

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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

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：日本語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

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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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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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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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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記述言語：日本語   掲載種別：研究論文（学術雑誌）

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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記述言語：日本語   掲載種別：研究論文（学術雑誌）

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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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

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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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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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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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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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）

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

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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）

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

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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.

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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

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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

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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

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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

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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/

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.

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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

Scopus

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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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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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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

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）

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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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

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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）

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

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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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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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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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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）

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

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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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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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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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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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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）

記述言語：英語   掲載種別：研究論文（学術雑誌）

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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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）

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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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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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）

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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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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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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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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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）

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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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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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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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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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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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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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）

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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その他リンク： https://www.jstage.jst.go.jp/article/sicetr/49/5/49_553/_pdf

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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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）

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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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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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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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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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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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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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

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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

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

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．

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

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.

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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

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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

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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

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

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．

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

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

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

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

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

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

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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）

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

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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

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

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開催期間： 2020年09月   記述言語：英語  

開催期間： 2020年09月   記述言語：日本語  

開催期間： 2020年09月   記述言語：日本語  

開催期間： 2020年09月   記述言語：日本語  

開催期間： 2020年09月   記述言語：英語  

開催期間： 2020年05月   記述言語：英語  

開催期間： 2020年05月   記述言語：英語  

開催期間： 2020年03月   記述言語：英語  

開催期間： 2020年03月   記述言語：英語  

開催期間： 2020年03月   記述言語：英語  

開催期間： 2020年03月   記述言語：英語  

開催期間： 2019年12月   記述言語：英語  

開催期間： 2019年12月   記述言語：日本語  

開催期間： 2019年12月   記述言語：英語  

開催期間： 2019年11月   記述言語：英語  

開催期間： 2019年10月   記述言語：英語  

開催期間： 2019年10月   記述言語：日本語  

開催期間： 2019年09月   記述言語：英語  

開催期間： 2019年09月   記述言語：日本語  

開催期間： 2019年09月   記述言語：日本語  

開催期間： 2019年09月   記述言語：日本語  

開催期間： 2019年09月   記述言語：日本語  

開催期間： 2019年07月   記述言語：日本語  

開催期間： 2019年07月   記述言語：日本語  

開催期間： 2019年07月   記述言語：日本語  

開催期間： 2019年05月   記述言語：英語  

開催期間： 2019年03月   記述言語：英語  

開催期間： 2019年03月   記述言語：日本語  

開催期間： 2019年03月   記述言語：日本語  

開催期間： 2019年02月   記述言語：英語  

開催期間： 2019年01月   記述言語：英語  

開催期間： 2019年01月   記述言語：英語  

開催期間： 2019年01月   記述言語：英語  

開催期間： 2018年12月   記述言語：英語  

開催期間： 2018年11月   記述言語：日本語  

開催期間： 2018年11月   記述言語：日本語  

開催期間： 2018年10月   記述言語：日本語  

開催期間： 2018年10月   記述言語：日本語  

開催期間： 2018年08月   記述言語：日本語  

開催期間： 2018年08月   記述言語：日本語  

開催期間： 2018年05月   記述言語：日本語  

開催期間： 2018年01月   記述言語：英語  

開催期間： 2017年11月   記述言語：日本語  

開催期間： 2017年09月   記述言語：日本語  

開催期間： 2017年08月   記述言語：日本語  

開催期間： 2017年03月   記述言語：日本語  

開催期間： 2016年12月   記述言語：英語  

開催期間： 2016年11月   記述言語：日本語  

開催期間： 2016年05月   記述言語：日本語  

開催期間： 2015年12月   記述言語：英語  

開催期間： 2015年08月   記述言語：英語  

開催期間： 2015年05月   記述言語：日本語  

開催期間： 2015年05月   記述言語：英語  

開催期間： 2015年04月   記述言語：英語  

開催期間： 2014年12月   記述言語：英語  

開催期間： 2014年07月   記述言語：英語  

開催期間： 2014年01月   記述言語：日本語  

開催期間： 2013年10月   記述言語：英語  

開催期間： 2013年07月   記述言語：英語  

開催期間： 2012年08月   記述言語：日本語  

開催期間： 2012年08月   記述言語：日本語  

開催期間： 2012年07月   記述言語：英語  

開催期間： 2012年05月   記述言語：日本語  

開催期間： 2012年01月   記述言語：日本語  

開催期間： 2012年01月   記述言語：日本語  

開催期間： 2011年11月   記述言語：英語  

開催期間： 2011年11月   記述言語：日本語  

開催期間： 2011年11月   記述言語：英語  

開催期間： 2011年09月   記述言語：英語  

開催期間： 2011年09月   記述言語：日本語  

開催期間： 2011年09月   記述言語：日本語  

開催期間： 2011年07月   記述言語：日本語  

開催期間： 2011年07月   記述言語：日本語  

開催期間： 2011年03月   記述言語：日本語  

開催期間： 2010年09月   記述言語：英語  

開催期間： 2010年06月   記述言語：日本語  

開催期間： 2010年02月   記述言語：英語  

開催期間： 2009年09月   記述言語：日本語  

開催期間： 2009年05月   記述言語：日本語  

開催期間： 2008年06月   記述言語：日本語  

開催期間： 2008年03月   記述言語：日本語  

開催期間： 2007年04月   記述言語：英語  

開催期間： 2006年09月   記述言語：日本語  

開催期間： 2006年06月   記述言語：英語  

開催期間： 2006年05月   記述言語：日本語  

開催期間： 2024年11月   記述言語：英語  

開催期間： 2024年10月   記述言語：日本語  

開催期間： 2024年10月   記述言語：英語  

開催期間： 2024年10月   記述言語：日本語  

開催期間： 2024年10月   記述言語：日本語  

開催期間： 2024年09月   記述言語：日本語  

開催期間： 2024年09月   記述言語：日本語  

開催期間： 2024年08月   記述言語：日本語  

開催期間： 2024年08月   記述言語：日本語  

開催期間： 2024年08月   記述言語：日本語  

開催期間： 2024年08月   記述言語：日本語  

開催期間： 2024年08月   記述言語：日本語  

開催期間： 2024年07月   記述言語：日本語  

開催期間： 2024年07月   記述言語：英語  

開催期間： 2024年03月   記述言語：日本語  

開催期間： 2024年01月   記述言語：英語  

開催期間： 2024年01月   記述言語：英語  

開催期間： 2024年01月   記述言語：英語  

開催期間： 2024年01月   記述言語：英語  

開催期間： 2023年09月   記述言語：日本語  

開催期間： 2023年09月   記述言語：日本語  

開催期間： 2023年09月   記述言語：日本語  

開催期間： 2023年09月   記述言語：日本語  

開催期間： 2023年07月   記述言語：日本語  

開催期間： 2023年07月   記述言語：日本語  

開催期間： 2023年07月   記述言語：日本語  

開催期間： 2023年07月   記述言語：英語  

開催期間： 2023年03月   記述言語：日本語  

開催期間： 2023年03月   記述言語：日本語  

開催期間： 2023年03月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年11月   記述言語：日本語  

開催期間： 2022年09月   記述言語：英語  

開催期間： 2022年09月   記述言語：日本語  

開催期間： 2022年09月   記述言語：日本語  

開催期間： 2022年09月   記述言語：日本語  

開催期間： 2022年07月   記述言語：英語  

開催期間： 2022年07月   記述言語：日本語  

開催期間： 2022年07月   記述言語：日本語  

出願番号：2022-566687  出願日：2022年06月07日

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 

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 

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 

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