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Proceedings Paper

Tracking vehicles in congested traffic
Author(s): David Beymer; Jitendra Malik
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Paper Abstract

For the problem of tracking vehicles on freeways using machine vision, existing systems work well in free-flowing traffic. Traffic engineers, however, are more interested in monitoring freeways when there is congestion, and current systems break down for congested traffic due to the problem of partial occlusion. We are developing a feature-based tracking approach for the task of tracking vehicles under congestion. Instead of tracking entire vehicles, vehicle sub-features are tracked to make the system robust to partial occlusion. In order to group together sub-features that come from the same vehicle, the constraint of common motion is used. In this paper we describe the system and experiments of our tracker/grouper on several minutes of videotape.

Paper Details

Date Published: 17 February 1997
PDF: 11 pages
Proc. SPIE 2902, Transportation Sensors and Controls: Collision Avoidance, Traffic Management, and ITS, (17 February 1997); doi: 10.1117/12.267150
Show Author Affiliations
David Beymer, Univ. of California/Berkeley (United States)
Jitendra Malik, Univ. of California/Berkeley (United States)


Published in SPIE Proceedings Vol. 2902:
Transportation Sensors and Controls: Collision Avoidance, Traffic Management, and ITS
Alan C. Chachich; Marten J. de Vries, Editor(s)

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