Internet supercomputing is becoming an increasingly popular means for harnessing the power of a vast number of interconnected computers. This comes at a cost substantially lower t...
Seda Davtyan, Kishori M. Konwar, Alexander A. Shva...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with som...
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
The application of frequent patterns in classification has demonstrated its power in recent studies. It often adopts a two-step approach: frequent pattern (or classification rule) ...