Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth - a parameter of the underlying graph structure. Computing the (m...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
We present a low-cost hand-based device coupled with a 3D motion recovery engine and 3D visualization. This platform aims at studying ergonomic 3D interactions in order to manipula...
Diane Lingrand, Philippe Renevier, Anne-Marie Pinn...
This paper provides a comprehensive analysis of exactly what visual information about the world is embedded within a single image of an eye. It turns out that the cornea of an eye...
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...