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Paper Abstract and Keywords
Presentation 2017-10-05 14:15
Automatic Segmentation using Graph Cuts based on Human Body Detection of Kinect V2
Kodai Kobayashi (Tokyo Metropolitan Univ), Masatoshi Sato (Tamagawa Univ), Takuya Asaka (Tokyo Metropolitan Univ) IE2017-50
Abstract (in Japanese) (See Japanese page) 
(in English) To quickly segment human body region in images or videos with high accuracy makes video surveillances and making composite images efficient. In conventional method, to segment region without location information given by users is difficult. In this paper, we present a novel method to automatically segment human body region by using Graph Cuts based on human body detection of Kinect V2. By applying expansion and contraction processing on the image of human body detection and automating labeling "seed", we can automate segmentation by Graph Cuts. The conventional methods of automatic segmentation have a problem of slow processing time. The proposed method can accelerate processing time by replacing Graph Cuts with Maximum-Flow Neural Network(MF-NN). When MF-NN is designed with the integrated circuit such as Programmable Logic Device, Memristor or Phase Change Memory which can change graph structure and branch conductance, the novel min-cut solution with real– time processing can be expected.
Keyword (in Japanese) (See Japanese page) 
(in English) Graph Cuts / segmentation / Kinect V2 / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 228, IE2017-50, pp. 19-24, Oct. 2017.
Paper # IE2017-50 
Date of Issue 2017-09-28 (IE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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)
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Conference Information
Committee IE ITE-ME ITE-AIT  
Conference Date 2017-10-05 - 2017-10-06 
Place (in Japanese) (See Japanese page) 
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Paper Information
Registration To IE 
Conference Code 2017-10-IE-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Segmentation using Graph Cuts based on Human Body Detection of Kinect V2 
Sub Title (in English)  
Keyword(1) Graph Cuts  
Keyword(2) segmentation  
Keyword(3) Kinect V2  
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1st Author's Name Kodai Kobayashi  
1st Author's Affiliation Tokyo Metropolitan University (Tokyo Metropolitan Univ)
2nd Author's Name Masatoshi Sato  
2nd Author's Affiliation Tamagawa University (Tamagawa Univ)
3rd Author's Name Takuya Asaka  
3rd Author's Affiliation Tokyo Metropolitan University (Tokyo Metropolitan Univ)
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Speaker Author-1 
Date Time 2017-10-05 14:15:00 
Presentation Time 25 minutes 
Registration for IE 
Paper # IE2017-50 
Volume (vol) vol.117 
Number (no) no.228 
Page pp.19-24 
#Pages
Date of Issue 2017-09-28 (IE) 


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