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In the last decades, Robust Principal Component Analysis (PCA) has been drawn much attention in the image processing, computer vision and machine learning communities and various robust PCA methods have been developed. This paper introduces a new generalized robust PCA with emphasizing on ℓ2, 1-norm minimization on loss function. The ℓ2, 1-norm instead of Frobenius norms based loss function is robust...
It is natural way to write Chinese characters by digital pen for foreign students, whose handwriting information is much richer than digital image. Stroke matching is the prerequisite to analyze handwriting errors of Chinese character. Present research hardly delivers the optimal solution of the problem on the growing sizes and complexity because of wide differences among learners' writing qualities...
Each year more and more people are diagnosed with Diabetes Mellitus. As this disease continues to grow, it will have an enormous effect on society. Recently, a computerized noninvasive diagnostic method was proposed using facial block color features with a sparse representation classifier. This method eliminated the need to extract bodily fluids, and any feelings of pain and discomfort associated...
We formulate multiple object tracking (MOT) as a Generalized Maximum Multi Clique problem (GMMCP) without any simplified version in problem formulation or optimization, which makes full use of image evidence. Afterwards, we solve the GMMCP through Mixed Binary-Integer Program (MBIP) and obtain the final motion trajectories of the multiple objects. In order to improve the algorithm's performance, we...
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