Looking around in our every day environment, many of the encountered objects are specular to some degree. Actively using this fact when reconstructing objects from image sequences...
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
One challenge for research in constraint-based scheduling has been to produce scalable solution procedures under fairly general representational assumptions. Quite often, the comp...
In order to reduce the rejection rate of our automatic reading system, we propose to pre-classify the business documents by introducing an Automatic Recognition of Documents stage...