We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
— This paper describes an improved methodology for human motion recognition and imitation based on Factorial Hidden Markov Models (FHMM). Unlike conventional Hidden Markov Models...
: This paper presents a general rst-order kinematic model of frictionless rigid-body contact for use in hybrid force motion control. It is formulated in an invariant manner by trea...
Roy Featherstone, Stef Sonck Thiebaut, Oussama Kha...