Temporal consistent real-time stereo for intelligent vehicles

Abstract

This paper presents a real-time stereo image sequences matching approach dedicated to intelligent vehicles applications. The main idea of the paper consists in integrating temporal information into the matching scheme. The estimation of the disparity map of an actual frame exploits the disparity map estimated for its preceding frame. An association between the two frames is searched, i.e. temporal integration. The disparity range is inferred for the actual frame based on both the association and the disparity map of the preceding frame. Dynamic programming technique is considered for matching the image features. As a similarity measure, a variance-based cost function is used. The proposed approach is tested on virtual and real stereo image sequences and the results are satisfactory. The method is fast and able to provide about 20 millions disparity maps per second on a HP Pavilion dv6700 2.1 GHZ.