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.
Tracking vehicles in congested traffic
1996-01-01
991299 byte
Conference paper
Electronic Resource
English
Tracking Vehicles in Congested Traffic
British Library Conference Proceedings | 1996
|Tracking vehicles in congested traffic
SPIE | 1997
|Approach for counting vehicles in congested traffic flow
SPIE | 2005
|Extracting Vehicle Trajectories Using Unmanned Aerial Vehicles in Congested Traffic Conditions
DOAJ | 2019
|