We show how to extend the ICP framework to nonrigid registration, while retaining the convergence properties of the original algorithm. The resulting optimal step nonrigid ICP fra...
Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper, we develop a discriminative framework for simultaneous se...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Many applications in computer vision and pattern recognition involve drawing inferences on certain manifoldvalued parameters. In order to develop accurate inference algorithms on ...
Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellap...
In this work we introduce a novel approach to object categorization that incorporates two types of context ? cooccurrence and relative location ? with local appearancebased featur...
Carolina Galleguillos, Andrew Rabinovich, Serge Be...