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Paper Abstract and Keywords
Presentation 2017-02-19 10:20
Research of Action Recognition for Automatic Internal State Estimation based on Deep Learning
Kanji Yamaguchi, Masayuki Kashima, Shinya Fukumoto, Kiminori Satou, Mutsumi Watanabe (kagoshima Univ.) PRMU2016-177 CNR2016-44
Abstract (in Japanese) (See Japanese page) 
(in English) Japan is turning into a high-stress society.Cause of stress are those that are in a state of mind taut by "anxiety-tension".Risk of various problems caused by stress cause are reduced and improved if Autometic recognition of anxiety tension is relized.In recent years, Deep Learning has been studied in various recognition problems from the success of image recognition and speech recognition.The purpose of this research is to estimate the tension state of the target person using Deep Learning from the moving images.However, to estimate the state of tension, it is necessary to recognize external information such as facial expression and behavior of the subject.Therefore, this paper aims to recognize the behavior of the target person from moving images, and also verifies and compares time series deep learning recognition.
From the results, it was found that the highest recognition performance is shown in 3D-Convolutional Neural Network.This indicates that feature learning for 3D-CNNs in the time direction is effective.
Keyword (in Japanese) (See Japanese page) 
(in English) Person's Internal state sstimation / Action recognition / Convolutional Neural Networks / 3D-Convolutional Neural Networks / Recurrent Neural Networks / Long Short Term Memory / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 461, PRMU2016-177, pp. 143-148, Feb. 2017.
Paper # PRMU2016-177 
Date of Issue 2017-02-11 (PRMU, CNR) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2016-177 CNR2016-44

Conference Information
Committee PRMU CNR  
Conference Date 2017-02-18 - 2017-02-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2017-02-PRMU-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Research of Action Recognition for Automatic Internal State Estimation based on Deep Learning 
Sub Title (in English)  
Keyword(1) Person's Internal state sstimation  
Keyword(2) Action recognition  
Keyword(3) Convolutional Neural Networks  
Keyword(4) 3D-Convolutional Neural Networks  
Keyword(5) Recurrent Neural Networks  
Keyword(6) Long Short Term Memory  
Keyword(7)  
Keyword(8)  
1st Author's Name Kanji Yamaguchi  
1st Author's Affiliation Kagoshima University (kagoshima Univ.)
2nd Author's Name Masayuki Kashima  
2nd Author's Affiliation Kagoshima University (kagoshima Univ.)
3rd Author's Name Shinya Fukumoto  
3rd Author's Affiliation Kagoshima University (kagoshima Univ.)
4th Author's Name Kiminori Satou  
4th Author's Affiliation Kagoshima University (kagoshima Univ.)
5th Author's Name Mutsumi Watanabe  
5th Author's Affiliation Kagoshima University (kagoshima Univ.)
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Speaker Author-1 
Date Time 2017-02-19 10:20:00 
Presentation Time 25 minutes 
Registration for PRMU 
Paper # PRMU2016-177, CNR2016-44 
Volume (vol) vol.116 
Number (no) no.461(PRMU), no.462(CNR) 
Page pp.143-148 
#Pages 6 
Date of Issue 2017-02-11 (PRMU, CNR) 

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