This paper presents a technique to learn dynamic appearance models from a small number of training frames. Under this framework, dynamic appearance is modelled as an unknown opera...
This paper presents a Bayesian approach to achieve efficient and accurate motion tracking in monocular image sequences. We first extract a deterministic motion model with six degr...
Background modeling and subtraction is a core component in motion analysis. The central idea behind such module is to create a probabilistic representation of the static scene tha...
Antoine Monnet, Anurag Mittal, Nikos Paragios, Vis...
Conditional Random Fields (CRFs) are popular models in computer vision for solving labeling problems such as image denoising. This paper tackles the rarely addressed but important ...
Patrick Pletscher, Sebastian Nowozin, Pushmeet Koh...
Visually extracted 2D and 3D information have their own advantages and disadvantages that complement each other. Therefore, it is important to be able to switch between the differ...
Emre Baseski, Nicolas Pugeault, Sinan Kalkan, Dirk...