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ICNC
2005
Springer

Multi-view Face Recognition with Min-Max Modular SVMs

9 years 1 months ago
Multi-view Face Recognition with Min-Max Modular SVMs
Abstract. Through task decomposition and module combination, minmax modular support vector machines (M3 -SVMs) can be successfully used for difficult pattern classification task. M3 -SVMs divide the training data set of the original problem to several sub-sets, and combine them to a series of sub-problems which can be trained more effectively. In this paper, we explore the use of M3 -SVMs in multi-view face recognition. Using M3 -SVMs, we can decompose the whole complicated problem of multiview face recognition into several simple sub-problems. The experimental results show that M3 -SVMs can be successfully used for multi-view face recognition and make the classification more accurate.
Zhi-Gang Fan, Bao-Liang Lu
Added 29 Jun 2010
Updated 29 Jun 2010
Type Conference
Year 2005
Where ICNC
Authors Zhi-Gang Fan, Bao-Liang Lu
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