Introduction - If you have any usage issues, please Google them yourself
In this paper, we present a comparison of four novel algorithms
that have been applied to the tracking of people in
an indoor scenario. Tracking is carried out in 3D or 2D
(ground plane) to provide position information for a variety
of surveillance, HCI or meeting-support services. The
algorithms, based on background subtraction, face detection,
particle filter feature-matching and edge alignment
of a cylindrical model are described and comparative results
presented using independent test data produced and
ground-truthed for the EU CHIL project.