Paper Abstract and Keywords |
Presentation |
2013-01-23 11:10
Co-segmentation based on Multiple-Instance Learning Jun Sakata, Toshikazu Wada (Wakayama Univ.) PRMU2012-90 MVE2012-55 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Appearance learning of an object represented by a text can be realized by utilizing image retrieval systems on the Internet. This enables us a real-world object search system, which searches real object providing a text representing the object. Images collected by an image retrieval system, however, cannot be used for appearance learning, because the object locations and sizes are not uniform among collected images. That is, object localization in each image is required. This problem can be taken as a co-segmentation problem extracting common object among images, and we propose a method based on Multiple-Instance Learning (MIL) framework. Our method consists of two parts, foreground-background modeling and discrete optimization to obtain object regions. Foreground-background modeling is to compute Diverse Density (DD) for excessively partitioned image regions, where original DD represents similarity among positive features and dissimilarity between negative features. In our method, we slightly modified the DD definition to fit the co-segmentation problem. Experimental results using iCoseg database demonstrates higher accuracy of our method than other methods. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Co-segmentation / iCoseg database / Multiple-Instance Learning / Diverse Density / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 385, PRMU2012-90, pp. 81-86, Jan. 2013. |
Paper # |
PRMU2012-90 |
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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PRMU2012-90 MVE2012-55 |
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 |
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Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Co-segmentation based on Multiple-Instance Learning |
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Co-segmentation |
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iCoseg database |
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Multiple-Instance Learning |
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Diverse Density |
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1st Author's Name |
Jun Sakata |
1st Author's Affiliation |
Wakayama University (Wakayama Univ.) |
2nd Author's Name |
Toshikazu Wada |
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Wakayama University (Wakayama Univ.) |
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Speaker |
Author-1 |
Date Time |
2013-01-23 11:10:00 |
Presentation Time |
30 minutes |
Registration for |
PRMU |
Paper # |
PRMU2012-90, MVE2012-55 |
Volume (vol) |
vol.112 |
Number (no) |
no.385(PRMU), no.386(MVE) |
Page |
pp.81-86 |
#Pages |
6 |
Date of Issue |
2013-01-16 (PRMU, MVE) |
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