Enhancing Exemplar SVMs using Part Level Transfer Regularization

Content based image retrieval (CBIR), the problem of searching digital images in large databases according to their visual content, is a well established research area in computer vision. In this work we are particularly interested in retrieving subwindows of images which are similar to the given query image, i.e. the goal is detection rather than image level classification. The notion of similarity is defined as being the same object class but also having similar viewpoint (e.g. frontal, left-facing, rear etc.). A query image can be a part of an object (e.g. head of a side facing horse), a complete object (e.g. frontal car image), or a composition of objects (visual phrases, e.g. person riding a horse). For instance, given a query of a horse facing left, the aim is to retrieve any left facing horse (intra-class variation) which might be walking or running with different feet formations (exemplar deformation).