Orthogonal Locality Minimizing Globality Maximizing Projections for Feature Extraction

(Dated: November 21, 2008) Abstract Locality Preserving Projections(LPP) is a recently developed linear feature extraction algorithm, which 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 on the geometrical meaning of the shift invariant LPP algorithm, we propose two novel 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.