The widely used engineering decisions concerning the performance of technological equipment for process industries are usually deterministic. Since the early 1990s probabilistic m...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Hough voting methods efficiently handle the high complexity of multiscale,
category-level object detection in cluttered scenes. The primary weakness
of this approach is however t...
Pradeep Yarlagadda, Antonio Monroy and Bjorn Ommer
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...