2009 International Conference on Business Intelligence and Financial Engineering A New Classification Method for PCA-Based Face Recognition Beijing, China July 24-July 26 ISBN: 978-0-7695-3705-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/BIFE.2009.107
This paper introduces a novel pattern classification approach called l1 norm nearest neighbor convex hull (l1 NNCH) approach and applies it for PCA-based face classification. In l1 NNCH, l1 norm distance from a query to a convex hull of a class is defined as the similarity of nearest neighbor rule. Principle component analysis (PCA), as an efficient technology for extracting feature, is applied to extract features of faces in this paper. Experimental results on the ORL and NJUST603 face databases show that l1NNCH combined with PCA has a good performance for face recognition.
Index Terms:
Classification, Data Mining, Nearest Neighbor, Convex Hull, PCA, Face Recognition.
Citation:
Xiaofei Zhou, Yong Shi, Peng Zhang, Guangli Nie, Wenhan Jiang, "A New Classification Method for PCA-Based Face Recognition," bife, pp.445-449, 2009 International Conference on Business Intelligence and Financial Engineering, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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