Multiple kernel collaborative representation based classification

摘要

At present, collaborative representation based classification (CRC) is widely used in many pattern classification and recognition tasks. Meanwhile, spatial pyramid matching (SPM) method, which considers the spatial information in representing the image, is efficient for image classification. However, for SPM, the weights to evaluate the representation of different subregions are fixed. In this paper, we combine CRC and multiple kernel learning approach, propose the multiple kernel collaborative representation based classification (MKCRC) method, and apply it to image classification to learn the weights of different subregions in representing the image. Experimental results have obvious advantages than state-of-the-art methods in several benchmark datasets, such as Caltech101, 102flowers, Scene 15 and UIUC sports.