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Paper Abstract and Keywords
Presentation 2005-10-28 09:30
Gender Recognition using multiple classifiers trained with sets of clustered features
Takahiko Kuwabara, Hitoshi Ikeda, Noriji Kato, Hirotsugu Kashimura (Fuji Xerox)
Abstract (in Japanese) (See Japanese page) 
(in English) Recognition of person's attributes (sex, age, and race, etc.) from the person's face image using machine learning technique has been researched. Person attribute recognition rate in real environment decreases greatly compared with that in controlled environment, because difference of face images caused from changes of lighting condition and face direction is usually larger than that caused from the attribute difference. In this research, we try to improve recognition rate under real environment using multiple classifiers with high recognition performance trained under specific environment. Feature vectors for training are extracted from face images taken in various environments, and divided to multiple groups by using the clustering technique. The feature vectors in each group are used to train individual classifiers. Moreover, performance degradation caused from cluster boundary is prevented by sharing training samples near the cluster boundary with related classifiers. Our method achieved gender recognition rate of 87.3% in real environment with 4-directional surface feature and a support vector machine.
Keyword (in Japanese) (See Japanese page) 
(in English) Face Image / Gender recognition / Clustering / / / / /  
Reference Info. IEICE Tech. Rep., vol. 105, no. 375, PRMU2005-93, pp. 1-6, Oct. 2005.
Paper # PRMU2005-93 
Date of Issue 2005-10-21 (PRMU) 
ISSN Print edition: ISSN 0913-5685
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Conference Information
Committee PRMU  
Conference Date 2005-10-27 - 2005-10-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2005-10-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Gender Recognition using multiple classifiers trained with sets of clustered features 
Sub Title (in English)  
Keyword(1) Face Image  
Keyword(2) Gender recognition  
Keyword(3) Clustering  
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1st Author's Name Takahiko Kuwabara  
1st Author's Affiliation Corporate Research Laboratory, Fuji Xerox Co., Ltd. (Fuji Xerox)
2nd Author's Name Hitoshi Ikeda  
2nd Author's Affiliation Corporate Research Laboratory, Fuji Xerox Co., Ltd. (Fuji Xerox)
3rd Author's Name Noriji Kato  
3rd Author's Affiliation Corporate Research Laboratory, Fuji Xerox Co., Ltd. (Fuji Xerox)
4th Author's Name Hirotsugu Kashimura  
4th Author's Affiliation Corporate Research Laboratory, Fuji Xerox Co., Ltd. (Fuji Xerox)
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Speaker Author-1 
Date Time 2005-10-28 09:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2005-93 
Volume (vol) vol.105 
Number (no) no.375 
Page pp.1-6 
#Pages
Date of Issue 2005-10-21 (PRMU) 


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