By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
Linear Discriminant Analysis (LDA) is a popular feature extraction technique for face recognition. However, It often suffers from the small sample size problem when dealing with t...
We introduce a new framework, namely Tensor Canonical Correlation Analysis (TCCA) which is an extension of classical Canonical Correlation Analysis (CCA) to multidimensional data ...
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
By representing images and image prototypes by linear subspaces spanned by "tangent vectors" (derivatives of an image with respect to translation, rotation, etc.), impre...
Nebojsa Jojic, Patrice Simard, Brendan J. Frey, Da...