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...
— In this paper a robotic catching algorithm based on a nonlinear mapping of visual information to the desired trajectory is proposed. The nonlinear mapping is optimized by learn...
This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. The proposed spatio-temporal object representation involves a set of distinct linea...
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Abstract. Most modern real-time strategy computer games have a sophisticated but fixed ‘AI’ component that controls the computer’s actions. Once the user has learned how suc...