Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
We present a top-down statistical modeling approach to explore the semantic structure in the American football video. First, a semantic space is defined where the video semantic ...
We propose a new two-stage framework for joint analysis of head gesture and speech prosody patterns of a speaker toward automatic realistic synthesis of head gestures from speech p...