Vision-based Lane-Vehicle Detection and Tracking

This chapter presents a vision‐based lane‐vehicle detection and tracking system comprising of (i) enhanced lane boundary detection, (ii) linear‐parabolic lane region tracking, and (iii) vehicle detection with a proposed possible vehicle region verification. First, a road image is partitioned into sky and road region. Lane boundaries are then extracted from the road region using line model estimation without applying Hough Transform. These detected boundaries are tracked in consecutive video frames with possible edges scanning and linear‐parabolic modeling. An approximate lane region is subsequently constructed with the predicted model parameters. By integrating the knowledge of lane region with vehicle detection, vehicle searching region is restricted to the road area so as to detect the shadow underneath a vehicle continuously with less interference to the road environment and non‐vehicle structures. A self‐adjusting bounding box is used to extract likely vehicle region for further verification. Besides horizontal symmetry detection, a vertical asymmetry measurement is presented to validate the extracted region and to obtain the center of frontal vehicle. Simulation results have revealed good performance of lane‐vehicle detection and tracking system.

[1]  C. Hoffmann,et al.  Fusing multiple 2D visual features for vehicle detection , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[2]  Cláudio Rosito Jung,et al.  A robust linear-parabolic model for lane following , 2004, Proceedings. 17th Brazilian Symposium on Computer Graphics and Image Processing.

[3]  Andrea Giachetti,et al.  The use of optical flow for road navigation , 1998, IEEE Trans. Robotics Autom..

[4]  José Manuel Pastor,et al.  IVVI: Intelligent vehicle based on visual information , 2007, Robotics Auton. Syst..

[5]  Nan Wang,et al.  Rear Vehicle Detection and Tracking for Lane Change Assist , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[6]  Weina Lu,et al.  A Synchronous Detection of the Road Boundary and Lane Marking for Intelligent Vehicles , 2007 .

[7]  Massimo Bertozzi,et al.  GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection , 1998, IEEE Trans. Image Process..

[8]  Chung-Lin Huang,et al.  Real-time vision-based preceding vehicle tracking and recognition , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[9]  Zehang Sun,et al.  On-road vehicle detection: a review , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.