Efficient tensor based face recognition
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This paper addresses the limitation of current multilinear PCA based techniques, in terms of prohibitive computational cost of testing and poor generalisation in some scenarios, when applied to large training databases. We define person-specific eigenmodes to obtain a set of projection bases, wherein a particular basis captures variation across lightings and viewpoints for a particular person. A new recognition approach is developed utilizing these bases. The proposed approach performs on a par with the existing multilinear approaches, whilst significantly reducing the complexity order of the testing algorithm.
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