This paper breaks with the common practice of using a joint state space representation and performing the joint data association in multi-object tracking. Instead, we present an i...
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...
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
Video query by semantic keywords is one of the most challenging research issues in video data management. To go beyond low-level similarity and access video data content by semanti...
Milind R. Naphade, Igor Kozintsev, Thomas S. Huang
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...