Faculty Profiles - ENOKIDA Shuichi

Papers - ENOKIDA Shuichi

Division display1 - 20 of about 83／ All the affair displays >>

Evaluating Learning Potential with Internal States in Deep Neural Networks Reviewed International journal

Shogo Takasaki, Shuichi Enokida

The 19th International Conference on Computer Vision Theory and Applications (VISAPP2024) 2024.02

Relationship Between Semantic Segmentation Model and Additional Features for 3D Point Clouds Obtained from on-Vehicle LIDAR Reviewed International journal

Hisato Hashimoto, Shuichi Enokida

The 19th International Conference on Computer Vision Theory and Applications (VISAPP2024) 2024.02

Current Status and Future Prospects of Real Traffic Flow Data Collection Technology for the Safety Assessment of Automatic Driving Using Measurement Vehicles

Taiji Hirayama, Kento Ohtani, Shuichi Enokida, Hiroki Matsubara

2024.02

Multi-Loss Weighting for Person Re-Identification Based on Deep Learning Reviewed

Yuya Shimizu, Shuichi Enokida

53 ( 1 ) 28 - 32 2024.01

Memory-Efficient Implementation of GMM-MRCoHOG for Human Recognition Hardware Reviewed International journal

Ryogo Takemoto, Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Yuichiro Tanaka, Shuichi Enokida, and Hakaru Tamukoh

The 18th International Conference on Computer Vision Theory and Applications (VISAPP2023) 2023.02

Hardware-Oriented Algorithm for Human Detection using GMM-MRCoHOG Features Reviewed International journal

Ryogo Takemoto, Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Yuichiro Tanaka, Shuichi Enokida, Hakaru Tamukoh

17th International Conference on Computer Vision Theory and Applications (VISAPP2022) 749 - 757 2022.02

3D MAP GENERATION WITH SHAPE AND APPEARANCE INFORMATION, Reviewed International journal

Taro Yamada, Shuichi Enokida

17th International Conference on Computer Vision Theory and Applications (VISAPP2022) 743 - 748 2022.02

Robust 3D Object Detection for Moving Objects Based on PointPillars Reviewed

Ryota Nakamura, Shuichi Enokida

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops 611 - 617 2022.01

Traffic situation analysis between Vehicle and Motorcycle safety at Malaysia Reviewed International journal

Hisashi Imanaga, Keisuke Fukuyama, Azhar Hamzah, Shuichi Enokida, Hajime Ishida

FISITA World Congress 2021 - Technical Programme 2021.09

A Dense Optical Flow Estimation Based on Dynamical System Approach under Intensity Variation Violating the Conservation Law Reviewed

Nakamura A., Sebe N., Enokida S., Nobuyama E.

2021 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2021 472 - 477 2021.09

Language：English Publishing type：Research paper (international conference proceedings)

Optical flow is a vector that represents the motion of objects in images. To estimate the optical flow, most of the optical flow estimation methods assume the intensity conservation law. The estimation methods based on a dynamical system approach [3], [4] also use the same assumption. Therefore, these methods might not be able to estimate correctly if the intensity conservation law is violated by various factors. A estimation model at a pixel considering the illumination change was proposed in [7] to improve the estimation accuracy in such situations. This paper proposes a new dense estimation model with the intensity correction quantity to overcome the estimation in the illumination change and the occlusion. Furthermore, this paper proposes to estimate the optical flow with the Kalman filter or the Kalman filter with the sparse constraint to correction quantity. Using the sparse constraint, the correction quantity becomes non-zero only near the flow boundaries. Accordingly, the improvement of estimation accuracy can expect. The effectiveness of the proposed models is demonstrated through numerical examples.

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85117685440&origin=inward

Traffic Situation Analysis for Vehicle to Motorcycle Safety at Malaysia (Second Report) Reviewed

Kawakoshi Maki, Imanaga Hisashi, Enokida Syuichi, Azhar Bin Hamzah, Ishida Hajime

Transactions of Society of Automotive Engineers of Japan ( Society of Automotive Engineers of Japan ) 52 ( 3 ) 707 - 713 2021.04

Language：Japanese Publishing type：Research paper (scientific journal)

The purpose of this study is to quantitatively understand the actual traffic situation between vehicle and motorcycle which is useful for preventing motorcycle accidents. From the video data recorded in Malaysia, we analyzed the behavior of motorcycles such as minimum distance between vehicles and minimum lane position in situations which can lead to rear-end collisions and head-on collisions which the number of vehicle-to-motorcycle fatal accidents in Malaysia is high. These results could help in the development of safety equipment to prevent motorcycle accidents.

DOI： 10.11351/jsaeronbun.52.707

CiNii Article

CiNii Research

A Hardware-oriented Algorithm of GMM-MRCoHOG for High-performance Human Detection by an FPGA Reviewed International journal

Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Shuichi Enokida, Hakaru Tamukoh

International Workshop on Advanced Image Technology 2021 (IWAIT2021) 2021.01

An FPGA Implementation of Human Recognition using MRCoHOG features Reviewed International journal

Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Shuichi Enokida, Hakaru Tamukoh

8th International Symposium on Applied Engineering and Science (SAES2020) 2020.12

Research on Feature descriptors for vehicle detection by LIDAR Reviewed

Takuma Oiwane, Priscilla Indira Osa, Shuichi Enokida

5th International Conference on Machine Vision and Machine Learning (MVML 2019) 107-1 - 107-8 2019.08

歩行者検出における混合正規分布を用いた状態空間の自律構成法 Reviewed

道下裕也, 東嵩士, 柴田雅聡, 村松竜弥, 山田英夫, 榎田修一

電気学会論文誌Ｃ 138 ( 9 ) 1100 - 1107 2018.09

Improving the Accuracy of Dynamical System Based Optical Flow Estimation by Central Difference Discretization of Time Derivative Reviewed

107-1 - 107-7 2018.08

Pedestrian Detection based on Gaussian Mixture Model Multiresolution CoHOG Reviewed

100-1 - 100-9 2018.08

LIDAR を用いた歩行者検出のためのReal AdaBoost に基づく特徴選択 Reviewed

髙田智, 榎田修一

自動車技術会論文集 49 ( 4 ) 799 - 805 2018.07

Fostering Professional Personnel for Intelligent Car and Robotics in Car-Robo Joint Graduate School Reviewed

Journal of JSEE 65 ( 4 ) 51 - 56 2017.08

Simultaneous Estimation of Optical Flow and its Boundaries based on the dynamical system model Reviewed

12th International Joint Conference on Computer Vision Theory and Applications (VISAPP2017) 377 - 385 2017.02

　PREV- NEXT 　

<ENOKIDA Shuichi>

Papers - ENOKIDA Shuichi