Rear Vehicle Detection and Tracking for Lane Change Assist

@article{Liu2007RearVD,
  title={Rear Vehicle Detection and Tracking for Lane Change Assist},
  author={Wei Liu and Xuezhi Wen and Bobo Duan and Huai Yuan and Nan Wang},
  journal={2007 IEEE Intelligent Vehicles Symposium},
  year={2007},
  pages={252-257}
}
A monocular vision based rear vehicle detection and tracking system is presented for Lane Change Assist (LCA), which does not need road boundary and lane information. Our algorithm extracts regions of interest (ROI) using the shadow underneath a vehicle, and accurately localizes vehicle regions in ROI by vehicle features such as symmetry, edge and shadow underneath vehicles. The algorithm realizes vehicle verification by combining knowledge-based and learning-based methods. During vehicle… CONTINUE READING
Highly Cited
This paper has 70 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 48 extracted citations

A comprehensive test framework to determine the spatial performance of camera-based vehicle detection algorithms

2014 13th International Conference on Control Automation Robotics & Vision (ICARCV) • 2014
View 5 Excerpts
Highly Influenced

Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis

IEEE Transactions on Intelligent Transportation Systems • 2013
View 6 Excerpts
Highly Influenced

On-road approaching motorcycle detection and tracking techniques: A survey

2013 IEEE International Conference on Control System, Computing and Engineering • 2013
View 5 Excerpts
Highly Influenced

Improved Vehicle Collision Avoidance System

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) • 2018

Overview of Environment Perception for Intelligent Vehicles

IEEE Transactions on Intelligent Transportation Systems • 2017
View 1 Excerpt

70 Citations

0510'10'13'16'19
Citations per Year
Semantic Scholar estimates that this publication has 70 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 14 references

Papanikolopoulos,“Real-Time Vehicle Following through a Novel Symmetry-Based Approach,

N. Y. Du
IEEE International Conference on Robotics & Automation • 1997
View 3 Excerpts
Highly Influenced

Front and rear vehicle detection and tracking in the day and night times using vision and sonar sensor fusion

2005 IEEE/RSJ International Conference on Intelligent Robots and Systems • 2005

Real-time vision-based preceding vehicle tracking and recognition

IEEE Proceedings. Intelligent Vehicles Symposium, 2005. • 2005
View 1 Excerpt

Vehicle detection combining gradient analysis and AdaBoost classification

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. • 2005
View 1 Excerpt

On-board vision system for lane recognition and front-vehicle detection to enhance driver's awareness

IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 • 2004

On-road vehicle detection using optical sensors: a review

Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749) • 2004
View 1 Excerpt

Vehicle detection fusing 2D visual features

IEEE Intelligent Vehicles Symposium, 2004 • 2004
View 1 Excerpt

A Robust Vehicle Detecting and Tracking System for Wet Weather Conditions Using the IMAP-VISION Image Processing Board

S. Kyo, T. Koga
IEEE International Conference on Intelligent Transportation Systems, pp. 423-428, 1999. • 1999
View 1 Excerpt

Similar Papers

Loading similar papers…