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Paper Abstract and Keywords
Presentation 2007-12-14 11:00
Ultra high speed image annotation/retrieval method by learning the conceptual relationship between images and labels
Hideki Nakayama, Tatsuya Harada, Yasuo Kuniyoshi (Tokyo Univ.), Nobuyuki Otsu (AIST) PRMU2007-147
Abstract (in Japanese) (See Japanese page) 
(in English) Content-based image recognition and retrieval are challenging
problems which have wide application.
In this paper, we propose a new method of image
annotation and retrieval which far surpasses the current state of the
art method based on SML on the standard benchmark database,
both in performance and computation speed.
Our method uses HLAC~(Higher-order Local Auto-Correlation)
features and probabilistic canonical correlation analysis to learn the
conceptual relationship between images and labels. It's notable that our
method performs recognition about 10,000 times faster than SML.
This achievement makes our method highly versatile and practical.
Keyword (in Japanese) (See Japanese page) 
(in English) Image Annotation/Retrieval / Probabilistic CCA / Higher-order Local Auto-Correlation Feature / / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 384, PRMU2007-147, pp. 65-70, Dec. 2007.
Paper # PRMU2007-147 
Date of Issue 2007-12-06 (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 PRMU2007-147

Conference Information
Committee PRMU  
Conference Date 2007-12-13 - 2007-12-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Kobe Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2007-12-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Ultra high speed image annotation/retrieval method by learning the conceptual relationship between images and labels 
Sub Title (in English)  
Keyword(1) Image Annotation/Retrieval  
Keyword(2) Probabilistic CCA  
Keyword(3) Higher-order Local Auto-Correlation Feature  
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1st Author's Name Hideki Nakayama  
1st Author's Affiliation The University of Tokyo (Tokyo Univ.)
2nd Author's Name Tatsuya Harada  
2nd Author's Affiliation The University of Tokyo (Tokyo Univ.)
3rd Author's Name Yasuo Kuniyoshi  
3rd Author's Affiliation The University of Tokyo (Tokyo Univ.)
4th Author's Name Nobuyuki Otsu  
4th Author's Affiliation National Institute of Advanced Industrial Science and Technology (AIST)
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Speaker Author-1 
Date Time 2007-12-14 11:00:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2007-147 
Volume (vol) vol.107 
Number (no) no.384 
Page pp.65-70 
#Pages 6 
Date of Issue 2007-12-06 (PRMU) 

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