Paper Abstract and Keywords |
Presentation |
2013-01-23 09:30
Face model creation based on simultaneous execution of hierarchical training-set clustering and common local feature extraction Takayuki Fukui, Toshikazu Wada, Hiroshi Oike, Jun Sakata (Wakayama Univ.) PRMU2012-84 MVE2012-49 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Face image retrieval based on local features has advantages of short elapsed time and robustness against the occlusions. However, the keypoint detection, beforehand with the feature description, may fail due to illumination change. For solving this problem, top-down model-based keypoint detection must be effective, where man-made face model does not fit for this task. This report addresses the problem of bottom-up face model creation from examples, which can be formalized as common local feature extraction among examples. For this purpose, a measure called Diverse Density (DD) established in the field of Multiple Instance Learning (MIL) can be applied. DD at a point in a feature space represents how the point is close to other positive examples while keeping enough distance from negative examples. Because of this this property, DD is defined as a product of metrics, which can easily be affected by exceptional data, i.e., if one negative data leaps into the neighbor of a positive example, the DD around there becomes lower. Actually, face images have wide variations of face organs’ positions, beard, mustache, glasses, and so on. Under these variations, DD for wide varieties of face images will be low at any point in the feature point. For solving this problem, we propose a method performing hierarchical clustering and common feature extraction simultaneously. In this method, DD score is employed as a measure representing the integrity of the face image set, and hierarchical clustering is performed by merging the cluster pair having maximum DD score. Through experiments on 1021 CASPEAL face images, we confirmed that multiple face models are successfully constructed. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Multiple Instance Learning / Diverse Density / hierarchical clustering / common image features / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 385, PRMU2012-84, pp. 23-28, Jan. 2013. |
Paper # |
PRMU2012-84 |
Date of Issue |
2013-01-16 (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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PRMU2012-84 MVE2012-49 |
Conference Information |
Committee |
PRMU MVE IPSJ-CVIM |
Conference Date |
2013-01-23 - 2013-01-24 |
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(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2013-01-PRMU-MVE-CVIM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Face model creation based on simultaneous execution of hierarchical training-set clustering and common local feature extraction |
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Keyword(1) |
Multiple Instance Learning |
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Diverse Density |
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hierarchical clustering |
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common image features |
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1st Author's Name |
Takayuki Fukui |
1st Author's Affiliation |
Wakayama University (Wakayama Univ.) |
2nd Author's Name |
Toshikazu Wada |
2nd Author's Affiliation |
Wakayama University (Wakayama Univ.) |
3rd Author's Name |
Hiroshi Oike |
3rd Author's Affiliation |
Wakayama University (Wakayama Univ.) |
4th Author's Name |
Jun Sakata |
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Wakayama University (Wakayama Univ.) |
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Speaker |
Author-1 |
Date Time |
2013-01-23 09:30:00 |
Presentation Time |
30 minutes |
Registration for |
PRMU |
Paper # |
PRMU2012-84, MVE2012-49 |
Volume (vol) |
vol.112 |
Number (no) |
no.385(PRMU), no.386(MVE) |
Page |
pp.23-28 |
#Pages |
6 |
Date of Issue |
2013-01-16 (PRMU, MVE) |
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