1. A computer-implemented method for identifying objects in images, wherein the method is performed by a processor, comprising: computing one or more interest points in each of a plurality of training images including one or more objects, wherein each interest point represents one pixel, and wherein the one or more interest points in a training image represent a subset of the pixels of the training image; extracting tokens associated with the interest points, wherein a token associated with an interest point comprises an image feature of an image region surrounding the interest point; comparing tokens associated with an interest point in a first training image with tokens associated with an interest point in a second training image to find matched tokens, wherein a matched token comprises a first token in the first training image and a second token in the second training image, and wherein the first token is related to the second token; grouping the matched tokens into sets, wherein a set comprises related matched tokens; computing a group token to represent each set of matched tokens; and creating a model tree using the group tokens, where each node of the tree represents an object model for identifying objects in images.