We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Conventional mutual information (MI)-based registration using pixel intensities is time-consuming and ignores spatial information, which can lead to misalignment. We propose a met...
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
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 paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...