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Paper Abstract and Keywords
Presentation 2014-03-14 10:45
Evaluation of image local features for the improvement of face tracking accuracy
Shogo Kawai, Maiya Hori, Hiroki Yoshimura, Yoshio Iwai (Tottori Univ.) PRMU2013-201
Abstract (in Japanese) (See Japanese page) 
(in English) We present local feature evaluation for a constrained local model (CLM) framework.
We target facial images captured by a mobile camera such as a smartphone.
When recognizing facial images captured by a mobile camera, changes in lighting conditions and image degradation from motion blur are considerable problems.
In the CLM framework, the optimization strategy is local expert-based deformable model fitting.
The likelihood of alignment at a particular landmark location is acquired beforehand using the local features of a large number of images and is used for estimating model parameters.
In this learning phase, the features and classifiers used have a great influence on the accuracy of estimation in landmark locations.
In our study, tracking accuracy can be improved by changing the features and classifiers for parts of the face.
In the experiments, the likelihood map was generated using various features and classifiers, and the accuracy of landmark locations was compared with the conventional method.
Keyword (in Japanese) (See Japanese page) 
(in English) Face tracking / Local feature / Classifier / Constrained Local Model (CLM) / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 493, PRMU2013-201, pp. 197-202, March 2014.
Paper # PRMU2013-201 
Date of Issue 2014-03-06 (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 PRMU2013-201

Conference Information
Committee PRMU  
Conference Date 2014-03-13 - 2014-03-14 
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 2014-03-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of image local features for the improvement of face tracking accuracy 
Sub Title (in English)  
Keyword(1) Face tracking  
Keyword(2) Local feature  
Keyword(3) Classifier  
Keyword(4) Constrained Local Model (CLM)  
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Keyword(6)  
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1st Author's Name Shogo Kawai  
1st Author's Affiliation Tottori University (Tottori Univ.)
2nd Author's Name Maiya Hori  
2nd Author's Affiliation Tottori University (Tottori Univ.)
3rd Author's Name Hiroki Yoshimura  
3rd Author's Affiliation Tottori University (Tottori Univ.)
4th Author's Name Yoshio Iwai  
4th Author's Affiliation Tottori University (Tottori Univ.)
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Speaker Author-1 
Date Time 2014-03-14 10:45:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2013-201 
Volume (vol) vol.113 
Number (no) no.493 
Page pp.197-202 
#Pages 6 
Date of Issue 2014-03-06 (PRMU) 

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