In this paper, we address the problem of learning an
adaptive appearance model for object tracking. In particular,
a class of tracking techniques called “tracking by detectionâ...
This paper deals with the problem of tracking multiple targets in a distributed network of self-configuring pan-tilt-zoom cameras. We focus on applications where events unfold over...
We have developed methods for segmentation and tracking of cells in time-lapse phase-contrast microscopy images. Our multi-object Bayesian algorithm detects and tracks large num...
David House, Matthew Walker, Zheng Wu, Joyce Wong,...
This paper presents a novel solution for flow-based tracking and 3D reconstruction of deforming objects in monocular image sequences. A non-rigid 3D object undergoing rotation and...
Lorenzo Torresani, Danny B. Yang, Eugene J. Alexan...
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...