@conference {12700, title = {Intra-personal kernel space for face recognition}, booktitle = {Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on}, year = {2004}, month = {2004/05//}, pages = {235 - 240}, abstract = {Intra-personal space modeling proposed by Moghaddam et al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the intra-personal spacce using a principal componen analysis and embedded in a probabilistic formulation. In this paper, we derive the principal subspace from the intro-personal kernel space by developing a probabilistic analysis for kernel principal components for face recognition. We test this algorithm on a subset of the FERET database with illumination and facial expression variations. The recognition performance demonstrates its advantage over other traditional subspace approaches.}, keywords = {analysis;, component, Expression, Face, facial, illumination, intra-personal, Kernel, lighting;, principal, probabilistic, probability;, recognition;, space;, variation;}, doi = {10.1109/AFGR.2004.1301537}, author = {Zhou,Shaohua and Chellapa, Rama and Moghaddam, B.} }