In this paper, we develop a Bayesian feedback method for incorporating global structure into prior models for binocular stereopsis. Since most stereo scenes contain either backgro...
In this paper, we investigate to which extent the "raw" mapping of Taylor series coefficients into jet-space can be used as a "language" for describing local i...
The scope of this paper is the interpretation of a user's intention via a video camera and a speech recognizer. In comparison to previous work which only takes into account g...
Invariance is an important aspect in image object recognition. We present results obtained with an extended tangent distance incorporated in a kernel density based Bayesian classi...
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...