In this paper we propose a novel computational method to infer visual saliency in images. The method is based on the idea that salient objects should have local characteristics tha...
This work presents a novel approach to content-based image retrieval in categorical multimedia databases. The images are indexed using a combination of text and content descriptor...
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
This paper addresses the problem of segmenting a textured mesh into objects or object classes, consistently with user-supplied seeds. We view this task as transductive learning and...
We introduce perturbation kernels, a new class of similarity measure for information retrieval that casts word similarity in terms of multi-task learning. Perturbation kernels mode...