Combining classifiers in rotated face space

Chen S., Shan T. and Lovell B.C. (2007). Combining classifiers in rotated face space. In: Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007. Australian Pattern Recognition Society (APRS), Glenelg, SA, (380-386). December 3, 2007-December 5, 2007. doi:10.1109/DICTA.2007.4426822


Author Chen S.
Shan T.
Lovell B.C.
Title of paper Combining classifiers in rotated face space
Conference name Australian Pattern Recognition Society (APRS)
Conference location Glenelg, SA
Conference dates December 3, 2007-December 5, 2007
Proceedings title Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007
Series Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007
Publication Year 2007
Sub-type Fully published paper
DOI 10.1109/DICTA.2007.4426822
ISBN 0769530672
Start page 380
End page 386
Total pages 7
Abstract/Summary Face recognition is a very complex classification problem due to nuisance variations in different conditions. Normally no single classifier can discriminate patterns well when unpredictable variations and a huge number of classes are involved. Combining multiple classifiers can improve discriminability over the best single classifier. In this paper, we present a way to combine classifiers for face recognition problem based on APCA classifiers. The proposed combinator generates various classifiers by rotating various face spaces and fusing them by applying a weighted distance measure. The combined classifier is tested on the Asian Face Database with 856 images. Experiments show a 30% reduction in classification error rate of our combined classifier and illustrates that combining classifiers from different face spaces may perform better than those based on a s ingle face space.
Subjects 1706 Computer Science Applications
1707 Computer Vision and Pattern Recognition
1709 Human-Computer Interaction
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Conference Paper
Collection: Scopus Import
 
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Created: Tue, 26 Nov 2013, 23:45:53 EST by System User