In this work we propose a probabilistic model for generic object classification from raw range images. Our approach supports a validation process in which classes are verified usi...
This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a po...
We propose a method to create process flow graphs automatically from textbooks for cooking programs. This is realized by understanding context by narrowing down the domain to cook...
We present an approach to spatial inference which is based on the procedural semantics of spatial relations. In contrast to qualitative reasoning, we do not use discrete symbolic m...
Sylvia Wiebrock, Lars Wittenburg, Ute Schmid, Frit...
Automatic content based schemes, as opposed to those with human endeavor, have become important as users attempt to organize massive data presented in the form of multimedia data ...