Ground-Image Plane Mapping for Lane marks detection

Abstract

Autonomous vehicles are equipped with optical sensors and micro-processing units to perform intelligent visual analysis of its surroundings. Due to the high speed of moving vehicle, the captured information has to be processed in a short duration to avoid possible collision. In this paper, aground-image plane mapping technique is proposed to quickly locate detected object if the object’s position is known in the real world. A three dimensional (3D) world coordinate is mathematically derived to an image plane using pinhole camera model. Several 3D perspective parameters such as vehicle’s steering angle and its velocity, sensor’s height and tilting angle are encompassed in the ground plane measurement. The optical sensor’s intrinsic parameters such as focal length, principal point, pixel’s height and width are also inserted for the mathematical model derivation. The importance of this ground to image plane mapping enables a rapid search of an object in a moving scene to achieve fast object identification during sensor acquisition. Experimental results have been carried on the application of lane marks detection with 93.82% correct mapping, using approximately 20% less processing time.