In this paper, we present a new multiple hypotheses tracking (MHT) approach. Our tracking method is suitable for online applications, because it labels objects at every frame and ...
In this paper, we present a probabilistic formulation of kernel-based tracking methods based upon maximum likelihood estimation. To this end, we view the coordinates for the pixel...
Quang Anh Nguyen, Antonio Robles-Kelly, Chunhua Sh...
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Visual tracking is still a challenging problem in computer vision. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. I...