Tensor Subspace Analysis

He, Xiaofei, Cai, Deng, Niyogi, Partha

Neural Information Processing Systems 

Previous work has demonstrated that the image variations of many objects (human faces in particular) under variable lighting can be effectively modeled by low dimensional linear spaces. The typical linear subspace learning algorithms include Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Locality Preserving Projection (LPP).

Similar Docs  Excel Report  more

TitleSimilaritySource
None found