Two-dimensional PCA: a new approach to appearance-based face representation and recognition
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Cites methods from "Two-dimensional PCA: a new approach..."
...2DPCA [29] is a simplified second-order tensorization of PCA and only optimizes one projection direction, while [30] and [25] are full formulations of the second-order tensorization of PCA....
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...Recently, a number of algorithms [25], [26], [27], [29], [30], [31] have been proposed to conduct dimensionality reduction on objects encoded as matrices or tensors of arbitrary order....
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References
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"Two-dimensional PCA: a new approach..." refers methods in this paper
...Within this context, Turk and Pentland [3] presented the well-known Eigenfaces method for face recognition in 1991....
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11,674 citations
"Two-dimensional PCA: a new approach..." refers methods in this paper
...The performance of 2DPCA was also compared with other methods, including Fisherfaces [16], ICA [13], [14], and Kernel Eigenfaces [14]....
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"Two-dimensional PCA: a new approach..." refers background in this paper
...4.2 Experiment on the AR Database The AR face database [ 17 ], [18] contains over 4,000 color face images of 126 people (70 men and 56 women), including frontal views of faces with different facial expressions, lighting conditions and occlusions....
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2,952 citations
"Two-dimensional PCA: a new approach..." refers background in this paper
...The AR face database [17], [18] contains over 4,000 color face images of 126 people (70 men and 56 women), including frontal views of faces with different facial expressions, lighting conditions and occlusions....
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2,934 citations
"Two-dimensional PCA: a new approach..." refers background in this paper
...However, Wiskott et al. [ 10 ] pointed out that PCA could not capture even the simplest invariance unless this information is explicitly provided in the training data....
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