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 |
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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PRMU2013-109 MVE2013-50 |
Conference Information |
Committee |
PRMU IPSJ-CVIM MVE |
Conference Date |
2014-01-23 - 2014-01-24 |
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(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) |
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Keyword(1) |
Action detection |
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Hough transform |
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Hough forests |
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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 |
6 |
Date of Issue |
2014-01-16 (PRMU, MVE) |
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