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Proceedings Paper

Uniform design based SVM model selection for face recognition
Author(s): Weihong Li; Lijuan Liu; Weiguo Gong
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Paper Abstract

Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460N (26 February 2010); doi: 10.1117/12.852806
Show Author Affiliations
Weihong Li, Chongqing Univ. (China)
Lijuan Liu, Chongqing Univ. (China)
Weiguo Gong, Chongqing Univ. (China)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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