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Robust principal component analysis for computer vision

Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference, (2001): 362-369vol.1

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Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares estimation techniques and hence fail to account for "outliers" which are common in re- alistic training sets. In computer vision applications, outliers typicall...更多

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