Adaptive Face Recognition via Structed Representation
Zhang, Yuhua, Zeng, Xiaoming · Acta Scientiarum Naturalium Universitatis Sunyatseni · 2014
In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspace approach to classify the test sample. In order to adapt all the cases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low sample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.