In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
Estimating the pose of an imaging sensor is a central research problem. Many solutions have been proposed for the case of a rigid environment. In contrast, we tackle the case of a...
Over the last several years, a new probabilistic representation for 3-d volumetric modeling has been developed. The main purpose of the model is to detect deviations from the norm...
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...