Laplacian principal components analysis (LPCA)

Details Laplacian principal components analysis (LPCA) Laplacian principal components analysis (LPCA)

2007-10-12

2011-11-22

Chang, Jon (Department: 2624)

Image analysis

Pattern recognition

C382S276000, C382S118000

Reexamination Certificate

active

08064697

ABSTRACT:
Systems and methods perform Laplacian Principal Components Analysis (LPCA). In one implementation, an exemplary system receives multidimensional data and reduces dimensionality of the data by locally optimizing a scatter of each local sample of the data. The optimization includes summing weighted distances between low dimensional representations of the data and a mean. The weights of the distances can be determined by a coding length of each local data sample. The system can globally align the locally optimized weighted scatters of the local samples and provide a global projection matrix. The LPCA improves performance of such applications as face recognition and manifold learning.

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