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Paper Abstract and Keywords
Presentation 2014-01-24 10:40
Trend-Sensitive Hough Forests: Action Detection Method Using Voting Trends
Kensho Hara, Takatsugu Hirayama, Kenji Mase (Nagoya Univ.) PRMU2013-109 MVE2013-50
Abstract (in Japanese) (See Japanese page) 
(in English) Action detection using the Hough voting approach can achieve robustness to occlusions because the approach casts votes for action classes and spatio-temporal action positions based on independent local features. However, each local feature has local information that tends to lead false votes. This paper uses a trend of the past voting to reduce false votes. We extend conventional Hough forests in order to use the trend. This extension can reduce false votes that conflict the trend. We called the proposed method Trend-Sensitive Hough Forests. In the experiment, we confirmed the decrease of false detection, so that the proposed method improved action detection accuracy compared with conventional Hough forests.
Keyword (in Japanese) (See Japanese page) 
(in English) Action detection / Hough transform / Hough forests / Voting trends / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 402, PRMU2013-109, pp. 177-182, Jan. 2014.
Paper # PRMU2013-109 
Date of Issue 2014-01-16 (PRMU, MVE) 
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 PRMU IPSJ-CVIM MVE  
Conference Date 2014-01-23 - 2014-01-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To PRMU 
Conference Code 2014-01-PRMU-CVIM-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Trend-Sensitive Hough Forests: Action Detection Method Using Voting Trends 
Sub Title (in English)  
Keyword(1) Action detection  
Keyword(2) Hough transform  
Keyword(3) Hough forests  
Keyword(4) Voting trends  
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1st Author's Name Kensho Hara  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Takatsugu Hirayama  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Kenji Mase  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2014-01-24 10:40:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2013-109, MVE2013-50 
Volume (vol) vol.113 
Number (no) no.402(PRMU), no.403(MVE) 
Page pp.177-182 
#Pages
Date of Issue 2014-01-16 (PRMU, MVE) 


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