Abstract
AbstractFace recognition has been a challenging task in computer vision. In this paper, we propose a new method for face recognition. Firstly, we extract HOG (Histogram of Orientated Gradient) features of each class face images in used Face databases. Then, we select the so-called eigenfaces from HOG features corresponding to each class face images and finally use them to build a overcomplete dictionary for ESRC (the Eigenface-based Sparse Representation Classification ). Experiments show that our method receives better results by comparison.Keywordsface recognitionhistogram of orientated gradientsparse representationESRC
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