This work investigates the use of nonlinear dependencies in natural image sequence statistics to learn higher-order structures in natural videos. We propose a two-layer model that...
Due to the intrinsic subtlety and dynamics of eye movements, automated generation of natural and engaging eye motion has been a challenging task for decades. In this paper we pres...
Learning dominant motion patterns or activities from a video is an important surveillance problem, especially in crowded environments like markets, subways etc., where tracking of...
In this paper, a motion-based approach for detecting high-level semantic events in video sequences is presented. Its main characteristic is its generic nature, i.e. it can be dire...
Recreating the temporal illumination variations of natural scenes has great potential for realistic synthesis of video sequences. In this paper, we present a 3D (model-based) appr...