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| Presentation | 2008-12-19 11:45 Multiclass VisualRank: Image Ranking Method in Clustered Subsets Based on Visual Features Mitsuru Ambai, Yuichi Yoshida (Denso IT Laboratory, Inc)  PRMU2008-178 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we propose Multiclass VisualRank, a method that expands the idea of VisualRank into more than one category of images. VisualRank uses visual features to refine ranking scores of images retrieved from image search engine; however, the results tend to be occupied by similar images. It is preferable that the top results include relevant yet diverse images. Multiclass VisualRank divides images retrieved from search engines into several categories based on distinctive patterns of visual features, and gives ranking within the category. This method displays the images in multiple sequences. Each of the sequence represents the image category and is sorted by their ranking scores. In this way, representative images that have distinct objects yet relate to the same search words are obtained. A clustering algorithm is applied to weighted graph derived from the visual similarities to extract clusters composed of similar images. Experimental results show that the proposed method can produce diverse results without losing precision. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | VisualRank / Image Retrieval / Clustering / Ranking / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 108, no. 363, PRMU2008-178, pp. 183-188, Dec. 2008. | |
| Paper # | PRMU2008-178 | |
| Date of Issue | 2008-12-11 (PRMU) | |
| 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) | |
| Download PDF | PRMU2008-178 |
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| Conference Information | |
| Committee | PRMU |
| Conference Date | 2008-12-18 - 2008-12-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kumamoto Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2008-12-PRMU |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multiclass VisualRank: Image Ranking Method in Clustered Subsets Based on Visual Features |
| Sub Title (in English) | |
| Keyword(1) | VisualRank |
| Keyword(2) | Image Retrieval |
| Keyword(3) | Clustering |
| Keyword(4) | Ranking |
| Keyword(5) | |
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| 1st Author's Name | Mitsuru Ambai |
| 1st Author's Affiliation | Denso IT Laboratory, Inc. (Denso IT Laboratory, Inc) |
| 2nd Author's Name | Yuichi Yoshida |
| 2nd Author's Affiliation | Denso IT Laboratory, Inc. (Denso IT Laboratory, Inc) |
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| Speaker | Author-1 |
| Date Time | 2008-12-19 11:45:00 |
| Presentation Time | 30 minutes |
| Registration for | PRMU |
| Paper # | PRMU2008-178 |
| Volume (vol) | vol.108 |
| Number (no) | no.363 |
| Page | pp.183-188 |
| #Pages | 6 |
| Date of Issue | 2008-12-11 (PRMU) |
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