1. A face recognition method on a computing device, comprising: obtaining a plurality of training face images which belongs to a plurality of face classes, wherein a face class includes one or more training face images and represents an identification of the one or more training face images; obtaining a plurality of training dictionaries corresponding to the plurality of training face images, wherein the plurality of training dictionaries include a plurality of deep feature matrices; obtaining an input face image; partitioning the input face image into a plurality of blocks; extracting corresponding deep feature vectors of the plurality of blocks of the input face image using a deep learning network; applying a collaborative representation model to represent the deep feature vectors of the blocks of the input face image with the training dictionaries and representation vectors; computing residual errors for the face classes, a residual error for a face class being a summation of errors for all blocks corresponding to the training face images in the face class, wherein an error for a block exists between a feature vector of the block in the input face image and the collaborative representation model of the block corresponding to the face class; classifying the input face image by selecting a face class that yields a minimum residual error as a recognition face class; and presenting the recognition face class of the input face image.