We propose a novel efficient algorithm for robust tracking of a fixed number of targets in real-time with low failure rate. The method is an instance of Sequential Importance Resa...
Abstract—This paper presents a hierarchical control architecture that enables cooperative surveillance by a heterogeneous aerial robot network comprised of mothership unmanned ai...
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
We propose a new method addressing the problem of template drift, a common phenomenon in which the target gradually shifts away from the template in object tracking. Much effort h...