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 |
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) |
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IE2017-50 |
Conference Information |
Committee |
IE ITE-ME ITE-AIT |
Conference Date |
2017-10-05 - 2017-10-06 |
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(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) |
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Graph Cuts |
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segmentation |
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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) |
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Takuya Asaka |
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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 |
6 |
Date of Issue |
2017-09-28 (IE) |
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