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Paper Abstract and Keywords
Presentation 2011-02-17 10:30
Automatic Image Annotation by Variational Random Forests
Motofumi Fukui, Noriji Kato, Qi Wenyuan (Fuji Xerox) PRMU2010-209
Abstract (in Japanese) (See Japanese page) 
(in English) Recently automatic image annotation (AIA) receives a lot of attention in the fields of information retrieval, and many ideas have been proposed over this decades. Semantic Multi-Class Labeling (SML[1]) is the representative example, based on a Naïve Bayes classifier with local image features whose existing probabilities are estimated by gaussian mixture models. However there is such a difficult problem that SML requires its long training time and annotation time, when a posterior distribution of each label is estimated. To deal with this problem, instead of gaussian mixture models, we introduce a Random Forest classifier into the AIA task. We have evaluated our method by using a standard image corpus. We show that the speed of annotating by our method is about 50 times faster than by SML, with maintaining the same performance as the existing ideas.
Keyword (in Japanese) (See Japanese page) 
(in English) Image Processing / Automatic Image Annotation / Image Retrieval / Random Forest / Generative Model / Probability / Classification /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 414, PRMU2010-209, pp. 7-12, Feb. 2011.
Paper # PRMU2010-209 
Date of Issue 2011-02-10 (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)
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Conference Information
Committee PRMU  
Conference Date 2011-02-17 - 2011-02-18 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2011-02-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Image Annotation by Variational Random Forests 
Sub Title (in English)  
Keyword(1) Image Processing  
Keyword(2) Automatic Image Annotation  
Keyword(3) Image Retrieval  
Keyword(4) Random Forest  
Keyword(5) Generative Model  
Keyword(6) Probability  
Keyword(7) Classification  
Keyword(8)  
1st Author's Name Motofumi Fukui  
1st Author's Affiliation Fuji Xerox Co., Ltd. (Fuji Xerox)
2nd Author's Name Noriji Kato  
2nd Author's Affiliation Fuji Xerox Co., Ltd. (Fuji Xerox)
3rd Author's Name Qi Wenyuan  
3rd Author's Affiliation Fuji Xerox Co., Ltd. (Fuji Xerox)
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Speaker Author-1 
Date Time 2011-02-17 10:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2010-209 
Volume (vol) vol.110 
Number (no) no.414 
Page pp.7-12 
#Pages 6 
Date of Issue 2011-02-10 (PRMU) 

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