Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Most tracking algorithms implicitly apply a coarse segmentation of each target object using a simple mask such as a rectangle or an ellipse. Although convenient, such coarse segme...
Tracking of multiple objects in biological image data is a challenging problem due largely to poor imaging conditions and complicated motion scenarios. Existing tracking algorithm...
In this paper we present a probabilistic framework for tracking regions based on their appearance. We exploit the feature-spatial distribution of a region representing an object a...
Ahmed M. Elgammal, Ramani Duraiswami, Larry S. Dav...