Recognising faces in unseen modes: A tensor based approach

This paper addresses the limitation of current multilinear techniques (multilinear PCA, multilinear ICA) when applied to face recognition for handling faces in unseen illumination and viewpoints. We propose a new recognition method, exploiting the interaction of all the subspaces resulting from multilinear decomposition (for both multilinear PCA and ICA), to produce a new basis called multilineareigenmodes. This basis offers the flexibility to handle face images at unseen illumination or viewpoints. Experiments on benchmarked datasets yield superior performance in terms of both accuracy and computational cost.

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh
• Keywords: Computer Vision, Current Multilinear Techniques, CVPR 2008, Multilinear Decomposition, Multilinear Ica, Multilinear Pca, Unseen Illumination