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Paper Abstract and Keywords
Presentation 2012-02-09 11:30
Face recognition based on virtual frontal view generation using LVTM with local patches clustering
Xi Li (Nagoya Univ.), Tomokazu Takahashi (Gifu Shotoku Gakuen Univ.), Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.) PRMU2011-191 SP2011-106
Abstract (in Japanese) (See Japanese page) 
(in English) One of the major difficulties encountered by face recognition is the varying poses caused by in-depth rotations. The intra-person appearance differences caused by rotations are often larger than the inter-person differences, which makes the traditional face recognition methods such as eigen-face infeasible. This paper presents a framework for face recognition
across pose based on virtual frontal view generation using Local View Transition Model(LVTM) with local patches clustering. Previous study on LVTM shows that more accurate appearance transition model can be achieved by first dividing the original face image plane into overlapping local patch regions and then the learned transition models for each patch are aggregated for the final transformation. In this paper we show that the accuracy the appearance transition model and the recognition rate can
be further improved by better exploiting the inherent linear relationship between frontal-nonfrontal face image pairs. This is achieved based on the observation that variations in appearance caused by pose are closely related to the corresponding 3D face structure and intuitively frontal-nonfrontal pairs from more similar local 3D face structures should have a stronger linear relationship. For each specific location, instead of learning a common transformation as in LVTM, the corresponding local
patches are first clustered based on appearance similarity distance metric and then the transition models are learned separately for each cluster. In the testing stage, each local patch for the input nonfrontal probe image is transformed using the learned local view transition model corresponding to the most visually similar cluster. The experimental results on real life face dataset demonstrate the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) face recognition / cross pose / view transition model / local patch / clustering / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 430, PRMU2011-191, pp. 31-36, Feb. 2012.
Paper # PRMU2011-191 
Date of Issue 2012-02-02 (PRMU, SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 PRMU2011-191 SP2011-106

Conference Information
Committee PRMU SP  
Conference Date 2012-02-09 - 2012-02-10 
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 2012-02-PRMU-SP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Face recognition based on virtual frontal view generation using LVTM with local patches clustering 
Sub Title (in English)  
Keyword(1) face recognition  
Keyword(2) cross pose  
Keyword(3) view transition model  
Keyword(4) local patch  
Keyword(5) clustering  
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1st Author's Name Xi Li  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Tomokazu Takahashi  
2nd Author's Affiliation Gifu Shotoku Gakuen University (Gifu Shotoku Gakuen Univ.)
3rd Author's Name Daisuke Deguchi  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Ichiro Ide  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Hiroshi Murase  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2012-02-09 11:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2011-191, SP2011-106 
Volume (vol) vol.111 
Number (no) no.430(PRMU), no.431(SP) 
Page pp.31-36 
#Pages
Date of Issue 2012-02-02 (PRMU, SP) 


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