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).
Neural Information Processing Systems
Dec-31-2006