An automatic extrinsic parameter calibration method for camera-on-vehicle on structured road

Author

Wu, Meng ; An, Xiangjing

Author_Institution

Autom. Inst. of Nat. Univ. of Defense Technol., Changsha

fYear

2007

fDate

13-15 Dec. 2007

Firstpage

1

Lastpage

5

Abstract

This paper proposes a novel self-calibration method for getting the extrinsic parameters of the camera on the autonomous vehicle. Basing on the model of the highway and the extrinsic parameters of the camera, the lane marking can be described parametrically in the vehicle coordinate system. The position and headings of the vehicle can be measured by itself in real time. Thus the Extended Kalman Filter can be applied to the kinematical model of the vehicle. By this means, it is possible to refine the original rough extrinsic parameters of the camera with an iterative way. Experiment results show that this method has a good performance in the structural scenery on highway.

Keywords

Kalman filters; automated highways; calibration; computer vision; image sequences; road vehicles; video cameras; automatic extrinsic parameter self-calibration method; autonomous road vehicle; camera-on-vehicle; computer vision; extended Kalman filter; highway model; image sequence; lane marking; vehicle kinematical model; Calibration; Cameras; Computer vision; Data mining; Land vehicles; Mobile robots; Prototypes; Remotely operated vehicles; Road transportation; Road vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Electronics and Safety, 2007. ICVES. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-1265-5

Electronic_ISBN

978-1-4244-1266-2

Type

conf

DOI

10.1109/ICVES.2007.4456379

Filename

4456379