In this paper we propose a robust visual tracking method
by casting tracking as a sparse approximation problem in a
particle filter framework. In this framework, occlusion, corru...
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
An algorithm is proposed for the purpose of optimizing the availability of files to an operating system prior to their being required during execution by a running system. This al...
This paper proposes a hash function family based on feature vocabularies and investigates the application in building indexes for image search. Each hash function is associated wi...