Representation-based classification and recognition, such as face recognition, have dominant performance in dealing with high-dimension data. However, for low-dimension data the classification results are not satisfying. This paper proposes a classification method based on nearest neighbor representation in feature space, which extends representation-based classification to nonlinear feature space, and also remedies its drawback in low-dimension data processing. First of all, the proposed method projects the data into a high-dimension space through a kernel function. Then, the test sample is r...
