Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
This paper describes a probabilistic model for coordination disambiguation integrated into syntactic and case structure analysis. Our model probabilistically assesses the parallel...
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Abstract. We present a tool developed for fostering probabilistic model checking of services formally specified in Scows, a stochastic enrichment of the Calculus for Orchestration ...
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...