Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Abstract. We address the validation of the current sensed environmental state against a model known from earlier perception. Our surface based approach compares 3D range data of a ...
Our goal is to turn an intensity image into its perceived luminance without parsing it into depths, surfaces, or scene illuminations. We start with jarring intensity differences at...
The usability of mobile robots for surveillance, search and rescue missions can be significantly improved by intelligent functionalities decreasing the cognitive load on the opera...
We present a simple technique to improve the perception of an object's shape. Bump mapping is well known in the computer graphics community for providing the impression of sm...