Online Extrinsic Parameters Calibration for Stereovision Systems Used in Far-Range Detection Vehicle Applications

Abstract

This paper presents a high-accuracy online calibration method for the absolute extrinsic parameters of a stereovision system that is suited for far-distance, vision-based vehicle applications. The method uses as prior knowledge the intrinsic parameters and the relative extrinsic parameters (relative position and orientation) of the two cameras, which are calibrated using offline procedures. These parameters remain unchanged if the two cameras are mounted on a rigid frame (stereo rig). The absolute extrinsic parameters define the position and orientation of the stereo system relative to a world coordinate system. They must be calibrated every time after mounting the stereo rig in the vehicle and are subject to changes due to static load factors for the used car setup. The proposed method is able to perform online the estimation of the absolute extrinsic parameters by driving the car on a flat and straight road, parallel with the longitudinal lane markers. The edge points of the longitudinal lane markers are extracted after a 2-D image classification process and reconstructed by stereovision in the stereo-rig coordinate system. After filtering out the noisy 3-D points, the normal vectors of the world coordinate system axes are estimated in the stereo-rig coordinate system by 3-D data fitting. The output of the method is the height and the orientation of the stereo cameras that are relative to the world coordinate system.