Low-rank regularized tensor discriminant representation for image set classification.
Signal Processing(2019)
摘要
•A general framework for learning discriminant representations of samples is proposed to better solve the classification of image sets.•Under the low-rank and the Grassmann assumptions, a latent space is obtained to capture the lowest-rank representations of samples.•An alternating direction algorithm based on ISTA is proposed to better ensure the convergence of the proposed model.
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关键词
Image set classification,Low-rank,Tensor discriminant representation,Grassmann manifold
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