Model-Based Object Tracking in Traffic Scenes
D. Koller,
K. Daniilidis,
T. Thorhallson, and H.-H. Nagel
In Proc. Second European Conference on Computer Vision, pp. 437-452, S. Margherita,
Ligure, Italy, May 18-23, 1992, LNCS 588, Springer-Verlag, 1992.
Abstract
This contribution addresses the problem of detection and tracking of
moving vehicles in image sequences from traffic scenes
recorded by a stationary camera.
In order to exploit the a priori knowledge about the shape and the
physical motion of vehicles in
traffic scenes, a parameterized vehicle model is used for an intraframe
matching process
and a recursive estimator based on a motion model is
used for motion estimation.
The initial guess about the position and orientation for the models are
computed with the help of a clustering approach of moving image features.
Shadow edges of the models are taken into account
in the matching process. This enables tracking of vehicles under complex
illumination conditions and within a small effective field of view.
Results on real world traffic scenes are presented and open problems are
outlined.
For a printed copy send email to koller@vision.caltech.edu
Last modified on Tuesday, November 20, 1996,
Dieter Koller
(koller@vision.caltech.edu)