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Paper Abstract and Keywords
Presentation 2013-03-11 12:00
Fundamental Study of Judging Sleeper's Turnovers from Depth Image Sequences by Support Vector Machine
Yuta Minezaki, Jun Ohya (Waseda Univ.) IMQ2012-53 IE2012-157 MVE2012-114 WIT2012-63
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, care of aged people’s turnovers is heavy burdens for helpers; in particular, automatic judgment of turnovers is desired. This paper proposes a method that can judge whether aged people being cared turned over by utilizing a depth image sequence acquired by Kinect sensor that observes the aged people in beds. Specifically, image features are extracted from aged people’s bodies in the depth image sequences, and are used for classification by Support Vector Machine. As the image features, this paper uses time series data of “xyz differences between left and right shoulders and between the left and right edges of the waist”, and “average depth in each block obtained by partitioning the bed area into w by h blocks” for exploring classification accuracies. Experimental results show that the former and latter features achieve 99.5% and 89.5% classification accuracies, respectively. The former gives a better accuracy, but its applicability is limited, while the latter can be applied for more general cases.
Keyword (in Japanese) (See Japanese page) 
(in English) Depth image / Support Vector Machine / human body posture estimation / image feature / detection of turnovers / care / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 473, IE2012-157, pp. 107-112, March 2013.
Paper # IE2012-157 
Date of Issue 2013-03-04 (IMQ, IE, MVE, WIT) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
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 IMQ2012-53 IE2012-157 MVE2012-114 WIT2012-63

Conference Information
Committee MVE IE WIT IMQ CQ  
Conference Date 2013-03-11 - 2013-03-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukuoka Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Quality of media communication, welfare, and general topics 
Paper Information
Registration To IE 
Conference Code 2013-03-MVE-IE-WIT-IMQ-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fundamental Study of Judging Sleeper's Turnovers from Depth Image Sequences by Support Vector Machine 
Sub Title (in English)  
Keyword(1) Depth image  
Keyword(2) Support Vector Machine  
Keyword(3) human body posture estimation  
Keyword(4) image feature  
Keyword(5) detection of turnovers  
Keyword(6) care  
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Keyword(8)  
1st Author's Name Yuta Minezaki  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Jun Ohya  
2nd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2013-03-11 12:00:00 
Presentation Time 25 minutes 
Registration for IE 
Paper # IMQ2012-53, IE2012-157, MVE2012-114, WIT2012-63 
Volume (vol) vol.112 
Number (no) no.472(IMQ), no.473(IE), no.474(MVE), no.475(WIT) 
Page pp.107-112 
#Pages 6 
Date of Issue 2013-03-04 (IMQ, IE, MVE, WIT) 

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