Random Subspace Two-Dimensional PCA for face recognition

Nguyen, Nam, Liu, Wanquan and Venkatesh, Svetha 2007, Random Subspace Two-Dimensional PCA for face recognition. In Horace, H.-S. Ip, Au, Oscar C., Leung, Howard, Sun, Ming-Ting, Ma, Wei-Ying and Hu, Shi-Min (ed), Advances in multimedia information processing--PCM 2007 : 8th Pacific Rim Conference on Multimedia, Hong Kong, China, December 11-14, 2007 : proceedings, Springer-Verlag, Berlin, Germany, pp.655-664, doi: 10.1007/978-3-540-77255-2_81.

Attached Files
Name Description MIMEType Size Downloads

Title Random Subspace Two-Dimensional PCA for face recognition
Author(s) Nguyen, Nam
Liu, Wanquan
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Title of book Advances in multimedia information processing--PCM 2007 : 8th Pacific Rim Conference on Multimedia, Hong Kong, China, December 11-14, 2007 : proceedings
Editor(s) Horace, H.-S. Ip
Au, Oscar C.
Leung, Howard
Sun, Ming-Ting
Ma, Wei-Ying
Hu, Shi-Min
Publication date 2007
Series Lecture notes in computer science ; 4810
Chapter number 81
Total chapters 98
Start page 655
End page 664
Total pages 10
Publisher Springer-Verlag
Place of Publication Berlin, Germany
Keyword(s) data structures
database systems
principal component analysis
problem solving
Summary The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA method in recognising human face. However, in many cases, this method tends to be overfitted to sample data. In this paper, we proposed a novel method named random subspace two-dimensional PCA (RS-2DPCA), which combines the 2DPCA method with the random subspace (RS) technique. The RS-2DPCA inherits the advantages of both the 2DPCA and RS technique, thus it can avoid the overfitting problem and achieve high recognition accuracy. Experimental results in three benchmark face data sets -the ORL database, the Yale face database and the extended Yale face database B - confirm our hypothesis that the RS-2DPCA is superior to the 2DPCA itself.
ISBN 9783540772545
3540772545
ISSN 0302-9743
Language eng
DOI 10.1007/978-3-540-77255-2_81
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1.1 Book chapter
Copyright notice ©2007, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044669

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 9 times in TR Web of Science
Scopus Citation Count Cited 10 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 567 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Fri, 20 Apr 2012, 13:24:20 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.