Robust obstacles detection and tracking using disparity for car driving assistance

摘要

This paper proposes a contribution for obstacles detection and tracking in the context of car-driving assistance. On the basis of the uv-disparity~9 designed for in-vehicle stereovision, we propose a robust procedure to detect the objects located on the road plane. This detection is used as an initialization stage for a real-time template matching procedure based on the minimizing of a weighted cost function. An appropriate update of the weights, based upon the quality of the previous matching and depth information, allows to track efficiently non-rigid objects in front of a clutter background . Sequences involving pedestrians are used to demonstrate the efficiency of our procedure.