venkatesh-robustlearning-2008.pdf (161.32 kB)
Robust learning of discriminative projection for multicategory classification on the Stiefel manifold
conference contribution
posted on 2008-01-01, 00:00 authored by D S Pham, Svetha VenkateshSvetha VenkateshLearning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in pose, illumination, and facial expression. To address this problem, we propose a framework formulated under statistical learning theory that facilitates robust learning of a discriminative projection. Dimensionality reduction using the projection matrix is combined with a linear classifier in the regularized framework of lasso regression. The projection matrix in conjunction with the classifier parameters are then found by solving an optimization problem over the Stiefel manifold. The experimental results on standard face databases suggest that the proposed method outperforms some recent regularized techniques when the number of training samples is small.
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Event
IEEE Conference on Computer Vision and Pattern Recognition (26th : 2008 : Anchorage, Alaska)Pagination
1 - 7Publisher
IEEELocation
Anchorage, AlaskaPlace of publication
Washington, D. C.Start date
2008-06-23End date
2008-06-28ISBN-13
9781424422425ISBN-10
1424422426Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2008, IEEETitle of proceedings
CVPR 2008 : Proceedings of the 26th IEEE Conference on Computer Vision and Pattern RecognitionUsage metrics
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