A practical stereo scheme for obstacle detection in automotive use

We propose a novel stereo scheme for obstacle detection which is aimed at practical automotive use. The basic methodology involves simple region matching between images, observed from a stereo camera rig, where it is assumed the images are related by a pseudo-projective transform. It provides an effective solution for determining boundaries of obstacles in noisy conditions, e.g. caused by weather or poor illumination, which conventional planar projection approaches cannot cope with. The linearity of the camera model also contributes significantly to compensation of road inclination. Essentially, precise lane detection and prior knowledge concerning obstacles or ambient conditions are unnecessary and the proposed scheme is therefore applicable to a wide variety of outdoor scenes. We have also developed a multi-VLIW processor that fulfills the essential specifications for automotive use. Our scheme for obstacle detection is largely reflected in the processor design so that real-time on-board processing can be realized with acceptable cost to both automobile users and manufacturers. The implementation of a prototype and experimental results illustrates our method.