Sensor networks are widely used in monitoring and tracking a large number of objects. Without prior knowledge on the dynamics of object distribution, their density estimation could...
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
We study the problem of tracking an object that is moving randomly through a dense network of wireless sensors. We assume that each sensor has a limited range for detecting the pr...
While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion,...
Global shape information is an effective top-down complement
to bottom-up figure-ground segmentation as well
as a useful constraint to avoid drift during adaptive tracking.
We p...