Title :
Robust classification and tracking of vehicles in traffic video streams
Author :
Morris, Brendan ; Trivedi, Mohan
Author_Institution :
Univ. of California San Diego, La Jolla, CA
Abstract :
The widespread use of cameras for traffic monitoring coupled with the availability of robust tracking algorithms has led to volumes of data. It is necessary to process this data for higher level tasks. One of these processing tasks is vehicle type classification, which can be used in a query based management system. This paper presents a tracking system with the ability to classify vehicles into three classes {sedan, semi, truck+SUV+van}. This system was developed after comparing classification schemes using both vehicle images and measurements. The most accurate of these learned classifiers was integrated into tracking software. This merging of classification and tracking greatly improved the accuracy on low resolution traffic video
Keywords :
automated highways; image classification; road traffic; road vehicles; target tracking; traffic engineering computing; video signal processing; video streaming; robust classification; robust tracking; traffic monitoring; traffic video streams; vehicle classification; vehicle tracking; Cameras; Image analysis; Layout; Linear discriminant analysis; Merging; Monitoring; Robustness; Streaming media; Telecommunication traffic; Vehicles;
Conference_Titel :
Intelligent Transportation Systems Conference, 2006. ITSC '06. IEEE
Conference_Location :
Toronto, Ont.
Print_ISBN :
1-4244-0093-7
Electronic_ISBN :
1-4244-0094-5
DOI :
10.1109/ITSC.2006.1707365