Nuclear Norm Based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes
Nuclear Norm Based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes
Recently, regression analysis has become a popular tool for face recognition. Most existing regression methods use the one-dimensional, pixel-based error model, which characterizes the representation error individually, pixel by pixel, and thus neglects the two-dimensional structure of the error image. We observe that occlusion and illumination changes generally lead, approximately, …