We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Most existing appearance models for visual tracking usually construct a pixel-based representation of object appearance so that they are incapable of fully capturing both global an...
Abstract. An important issue in tracking is how to incorporate an appropriate degree of adaptivity into the observation model. Without any adaptivity, tracking fails when object pr...
Andrew Blake, Jaco Vermaak, Michel Gangnet, Patric...
We present a framework that retains ambiguity in feature matching to increase the performance of 3D object recognition systems. Whereas previous systems removed ambiguous correspo...