A Tensor Based Isometric Projection Algorithm

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Data manifold represented in the reality is intrinsically in tensor form and so tensor-based subspace algorithms can preserve the intrinsic spatial structure information. They are beneficial for data representation and classification and have been widely used in recent years. In this paper, a new algorithm called Tensor based Isometric Projection (TIsoProjection) is proposed. The proposed algorithm can naturally describe the spatial relationship between the column vectors and the row vectors. Also it solves the small sample size (SSS) problem. Experiments on the ORL and YaleB demonstrate that the proposed algorithm can achieve higher recognition rate.

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183-188

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June 2012

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