In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez
In this paper, we define an observation model based on optical flow information to track objects using particle filter algorithms. Although the optical flow information enables us...
This paper presents two techniques for improving human body tracking within the particle filtering scheme. Both techniques explore the use of auxiliary measurements. The first tec...
To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
We present a comprehensive treatment of 3D object tracking by posing it as a nonlinear state estimation problem. The measurements are derived using the outputs of shape-encoded fi...