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Low-rank matrix completion has recently emerged in computational data analysis. The problem aims to recover a low-rank representation from the contaminated data. The errors in data are assumed to be sparse, which is generally characterized by minimizing the L1-norm of the residual. This actually assumes that the residual follows the Laplacian distribution. The Laplacian assumption, however, may not...
In this paper we present a novel approach of face identification by formulating the pattern recognition problem in terms of linear regression. Using a fundamental concept that patterns from a single object class lie on a linear subspace, we develop a linear model representing a probe image as a linear combination of class specific galleries. The inverse problem is solved using the least squares method...
The eyes are the most important facial landmarks on human face, for both human computer communication and face normalization. It is crucial to detect and locate the eyes accurately. This paper introduces a novel and simple method for eye localization. Based on the special gray lever distribution in the eye region, the spectral residual model is exploited to extract the rough eye region primarily....
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