Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2011-12-16 16:00
Image Annotation Using Adapted Gaussian Mixture Model
Yukihiro Tsuboshita, Noriji Kato (Fuji Xerox), Masato Okada (The Univ. of Tokyo) PRMU2011-144
Abstract (in Japanese) (See Japanese page) 
(in English) In the present study, we focus on learning based automatic image annotation method using Gaussian mixture model (GMM) as a probabilistic model. In Supervised Multiclass Labeling (SML), which is a conventional image annotation method to use GMM, training samples assigned to each semantic label are collected separately, and each probabilistic model of semantic labels is trained independently. The number of training samples therefore varies a great deal according to the labels. Consequently, there is a problem of low performances of semantic labels that have a few training samples because of over fitting. In the present study, we propose to introduce a penalty term using training samples that is not confined by a particular semantic label when training each semantic label model. According to the proposed method, while each probabilistic model to semantic labels is trained independently, optimization of whole annotation system is achieved, and the over fitting of models of labels that have a few samples is suppressed. As the result of evaluation tests using a standard test collection for image annotation, we found the proposed method exhibited higher performance than the conventional SML, especially recall and N+.
Keyword (in Japanese) (See Japanese page) 
(in English) Automatic Image Annotation / Machine Learning / Gaussian Mixture Model / Penalty Term / / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 353, PRMU2011-144, pp. 113-118, Dec. 2011.
Paper # PRMU2011-144 
Date of Issue 2011-12-08 (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 PRMU2011-144

Conference Information
Committee PRMU FM  
Conference Date 2011-12-15 - 2011-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Hamamatsu Campus, Shizuoka Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2011-12-PRMU-FM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Image Annotation Using Adapted Gaussian Mixture Model 
Sub Title (in English)  
Keyword(1) Automatic Image Annotation  
Keyword(2) Machine Learning  
Keyword(3) Gaussian Mixture Model  
Keyword(4) Penalty Term  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yukihiro Tsuboshita  
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 Masato Okada  
3rd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2011-12-16 16:00:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2011-144 
Volume (vol) vol.111 
Number (no) no.353 
Page pp.113-118 
#Pages 6 
Date of Issue 2011-12-08 (PRMU) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan