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Optical Engineering

Maximum variance projections for face recognition
Author(s): Tianhao Zhang; Jie Yang; Huahua Wang; Chunhua Du
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Paper Abstract

Maximum variance projection (MVP), as a novel subspace learning algorithm, is proposed. It is a linear discriminant algorithm that preserves local information by capturing the local geometry of the manifold. Two abilities of manifold learning and classification are combined into the properties of our algorithm. Since face images often belong to a submanifold of intrinsically low dimension, we carry out the MVP algorithm for face manifold learning and classification. Several experiments show the effectiveness of our developed algorithm.

Paper Details

Date Published: 1 June 2007
PDF: 8 pages
Opt. Eng. 46(6) 067206 doi: 10.1117/1.2746880
Published in: Optical Engineering Volume 46, Issue 6
Show Author Affiliations
Tianhao Zhang, Shanghai Jiao Tong Univ. (China)
Jie Yang, Shanghai Jiao Tong Univ. (China)
Huahua Wang, Shanghai Jiao Tong Univ. (China)
Chunhua Du, Shanghai Jiao Tong Univ. (China)

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