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Canonical correlations analysis (CCA) is often used for feature extraction and dimensionality reduction. However, the image vectorization of CCA breaks the spatial structure of the original image, and the excessive dimensions of vectors often cause the curse of dimensionality problem. In this paper, we propose a novel feature extraction method based on CCA in multi-linear discriminant subspace by...
This letter addresses the problem of analyzing spatio–temporal patterns for action recognition. In this letter we organize the whole training set in a single tensor, with each mode indicating one factor which influences the result of recognition, e.g., various view points. A novel method is proposed for tensor decomposition by discriminant analysis of multiscale features which represent the motion...
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