We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between...
We attack the problem of image-based rendering with occlusions and general camera motions by using distorted multiperspective images; such images provide multiple-viewpoint photom...
This paper shows how a recently introduced class of applications can be solved by constraint programming. This new type of application is due to the emergence of special real-time...
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
This paper outlines a generic, core temporal object model that provides support for the modeling of temporal object roles. This model draws from notions introduced in some of our ...