Model-Based Object Tracking in Monocular Image Sequences of Road Traffic Scenes
and H.-H. Nagel
International Journal of Computer Vision 10:3 (1993) 257-281.
Moving vehicles are detected and tracked automatically in monocular
image sequences from road traffic scenes recorded by a stationary
camera. In order to exploit the a priori knowledge about shape and
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. An
interpretation cycle supports the intraframe matching process with a
state MAP-update step. Initial model hypotheses are generated using
an image segmentation component which clusters coherently
moving image features into candidate representations of images of a
moving vehicle. The inclusion of an illumination model allows to take
shadow edges of the vehicle into account during the matching process.
Only such an elaborate combination of various techniques has enabled
us to track vehicles under complex illumination conditions and over
long (over 400 frames) monocular image sequences. Results on various
real world road traffic scenes are presented and open problems as well
as future work are outlined.
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Last modified on Tuesday, November 20, 1996,