We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
In this paper, we propose a panorama-based object tracking scheme for wide-view surveillance systems that can detect and track moving objects with a pan-tilt camera. A dynamic mosa...
One of the main difficult problem in video analysis is to track moving objects during a video sequence, especially in presence of occlusions. Unfortunately, almost all the differ...
Visual tracking is one of the central problems in computer vision. A crucial problem of tracking is how to represent the object. Traditional appearance-based trackers are using inc...
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is gener...