Paper Abstract and Keywords |
Presentation |
2012-09-02 10:30
q-Gaussian Mixture Models for Video Semantic Indexing Nakamasa Inoue, Koichi Shinoda (Tokyo Inst. of Tech.) PRMU2012-34 IBISML2012-17 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Gaussian mixture models (GMMs) which extend the bag-of-visual-words (BoW) to a probabilistic framework have been proved to be effective for image and video semantic indexing. Recently, the q-Gaussian distribution, which is derived in the non-extensive statistics, has been shown to be useful for representing patterns in many complex systems in physics such as fractals and cosmology. We propose q-Gaussian mixture models (q-GMMs), which are mixture models of q-Gaussian distributions, for image and video semantic indexing. It has a parameter q to control its tail-heaviness. The long-tailed distributions obtained for q>1 are expected to effectively represent complexly correlated data, and hence, to improve robustness against outliers. In our experiments, our proposed method outperformed the BoW method and achieved 49.4% and 10.9% in Mean Average Precision on the PASCAL VOC 2010 dataset and the TRECVID 2010 Semantic Indexing dataset, respectively. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
video search / semantic indexing / Gaussian mixture model / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 197, PRMU2012-34, pp. 31-36, Sept. 2012. |
Paper # |
PRMU2012-34 |
Date of Issue |
2012-08-26 (PRMU, IBISML) |
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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PRMU2012-34 IBISML2012-17 |
Conference Information |
Committee |
PRMU IBISML IPSJ-CVIM |
Conference Date |
2012-09-02 - 2012-09-03 |
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(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2012-09-PRMU-IBISML-CVIM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
q-Gaussian Mixture Models for Video Semantic Indexing |
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video search |
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semantic indexing |
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Gaussian mixture model |
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1st Author's Name |
Nakamasa Inoue |
1st Author's Affiliation |
Tokyo Institute of Technology (Tokyo Inst. of Tech.) |
2nd Author's Name |
Koichi Shinoda |
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Tokyo Institute of Technology (Tokyo Inst. of Tech.) |
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Speaker |
Author-1 |
Date Time |
2012-09-02 10:30:00 |
Presentation Time |
30 minutes |
Registration for |
PRMU |
Paper # |
PRMU2012-34, IBISML2012-17 |
Volume (vol) |
vol.112 |
Number (no) |
no.197(PRMU), no.198(IBISML) |
Page |
pp.31-36 |
#Pages |
6 |
Date of Issue |
2012-08-26 (PRMU, IBISML) |
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