A Real-time Computer Vision System for Measuring Traffic Parameters (1997)
| Venue: | in Computer Vision and Pattern Recognition |
| Citations: | 77 - 5 self |
BibTeX
@INPROCEEDINGS{Beymer97areal-time,
author = {David Beymer and Philip Mclauchlan and Benn Coifman and Jitendra Malik},
title = {A Real-time Computer Vision System for Measuring Traffic Parameters},
booktitle = {in Computer Vision and Pattern Recognition},
year = {1997},
pages = {495--501}
}
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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 featurebased 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, a real-time implementation using a network of DSP chips, and experiments of the system on approximately 44 lane hours of video data. 1 Introduction Traffic management and information systems must rely on a system of sensors for estimating traffic parameters in real-time. Currently, the dominant technology for ...
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