We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
Graham Taylor, Leonid Sigal, David Fleet, Geoffrey...
Characteristics of the 2D shape deformation in human motion contain rich information for human identification and pose estimation. In this paper, we introduce a framework for sim...
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks object by maximizing the similarity betwe...
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...