This paper presents a Sparse Representation Classification method for Face Recognition Based on Constraint Sampling and Face Alignment. The method combines texture and shape features to significantly improve the recognition rate. Tests show that the combined constraint sampling and facial alignment achieves very high recognition accuracy on both the AR face database (99.52%) and the CAS-PEAL face database (99.54%).
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