DocumentCode
870318
Title
On-road vehicle detection: a review
Author
Sun, Zehang ; Bebis, George ; Miller, Ronald
Author_Institution
ETreppid Technol., Reno, NV, USA
Volume
28
Issue
5
fYear
2006
fDate
5/1/2006 12:00:00 AM
Firstpage
694
Lastpage
711
Abstract
Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.
Keywords
automobiles; driver information systems; object detection; optical sensors; road accidents; intelligent vehicle; on-board automotive driver assistance systems; on-road vehicle detection; optical sensors; temporal continuity; Accidents; Automotive engineering; Intelligent sensors; Intelligent vehicles; Mobile robots; Remotely operated vehicles; Road vehicles; Robustness; Vehicle detection; Vehicle driving; Vehicle detection; computer vision; intelligent vehicles.; Accidents, Traffic; Algorithms; Artificial Intelligence; Automobile Driving; Automobiles; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Safety;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2006.104
Filename
1608034
Link To Document