Research on Technology of Compressed Sensing for Face Recognition

Donoho and Candes proposed the theory of compressive sensing which mainly based on the linear model, the core assumption is sparse signal. This theory has been successfully applying to process audio signal. It appears rapidly in the field of image processing (including face recognition), which raised the research upsurge of technology. Nowadays, the most classic algorithm is Representation-based Classification (SRC) in the field of face recognition. In this paper, in the basic of keeping the advantage of original SRC, by the way of linear segmentation and pair math the original graph, which effectively solved the conversion of data from high dimension to lower. At the same time, it also improved the performance and the recognition rate of algorithm in the occlusion and noise conditions.