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Optimal metric selection for improved multi-pose face recognition with group information

Zhang, Xin, Pham, Duc-Son, Liu, Wanquan and Venkatesh, Svetha 2012, Optimal metric selection for improved multi-pose face recognition with group information, in ICPR 2012 : Proceedings of 21st International Conference on Pattern Recognition, ICPR Organizing Committee, Tsubuka Science City, Japan, pp. 1675-1678.

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Title Optimal metric selection for improved multi-pose face recognition with group information
Author(s) Zhang, Xin
Pham, Duc-Son
Liu, Wanquan
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name International Conference on Pattern Recognition (21st : 2012 : Tsukuba Science City, Japan)
Conference location Tsubuka Science City, Japan
Conference dates 11-15 Nov. 2012
Title of proceedings ICPR 2012 : Proceedings of 21st International Conference on Pattern Recognition
Editor(s) [Unknown]
Publication date 2012
Conference series International Conference on Pattern Recognition
Start page 1675
End page 1678
Total pages 4
Publisher ICPR Organizing Committee
Place of publication Tsubuka Science City, Japan
Keyword(s) face recognition
image classification
image representation
Summary We address the limitation of sparse representation based classification with group information for multi-pose face recognition. First, we observe that the key issue of such classification problem lies in the choice of the metric norm of the residual vectors, which represent the fitness of each class. Then we point out that limitation of the current sparse representation classification algorithms is the wrong choice of the ℓ2 norm, which does not match with data statistics as these residual values may be considerably non-Gaussian. We propose an explicit but effective solution using ℓp norm and explain theoretically and numerically why such metric norm would be able to suppress outliers and thus can significantly improve classification performance comparable to the state-of-arts algorithms on some challenging datasets
ISBN 9784990644109
Language eng
Field of Research 080104 Computer Vision
080109 Pattern Recognition and Data Mining
Socio Economic Objective 899999 Information and Communication Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30052646

Document type: Conference Paper
Collection: Centre for Pattern Recognition and Data Analytics
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