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Optical Engineering

Orthogonal locality minimizing globality maximizing projections for feature extraction
Author(s): Feiping Nie; Shiming Xiang; Yangqiu Song; Changshui Zhang
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Paper Abstract

Locality preserving projections (LPP) is a recently developed linear-feature extraction algorithm that has been frequently used in the task of face recognition and other applications. However, LPP does not satisfy the shift-invariance property, which should be satisfied by a linear-feature extraction algorithm. In this paper, we analyze the reason and derive the shift-invariant LPP algorithm. Based on the analysis of the geometrical meaning of the shift-invariant LPP algorithm, we propose two algorithms to minimize the locality and maximize the globality under an orthogonal projection matrix. Experimental results on face recognition are presented to demonstrate the effectiveness of the proposed algorithms.

Paper Details

Date Published: 1 January 2009
PDF: 5 pages
Opt. Eng. 48(1) 017202 doi: 10.1117/1.3067869
Published in: Optical Engineering Volume 48, Issue 1
Show Author Affiliations
Feiping Nie, Tsinghua Univ. (China)
Shiming Xiang, Tsinghua Univ. (China)
Yangqiu Song, Tsinghua Univ. (China)
Changshui Zhang, Tsinghua Univ. (China)


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