Abstract
Multi-resolution small sample face recognition has always been a challenge in the field of face recognition. This paper proposes a multi-resolution small sample face recognition method based on coupled dictionary learning (MCDL). To expose the relationship between the representation coefficients corresponding to dictionary atoms and samples at different resolutions, MCDL introduces an analysis dictionary and jointly learns it with the synthesis dictionary. Besides, various coding coefficients are applied to each sample with varied resolutions throughout the multi-dictionary learning process so that the learnt dictionary is more realistic. Furthermore, we introduce the fractional norm into the model to remove the redundant information. Experimental results show that MCDL achieves good results and its recognition rate is higher than that of many algorithms.
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