In this paper, we present a simple algorithm for obstacle detection, road surface extraction and tracking using Kalman filter and u-v-disparity images. The proposed approach is based on the use of an unsynchronized camera system and the use of sparse maps instead of dense ones due to the unsynchronization constraint. First, a sparse disparity map is computed from two images then the u-v-disparity images are built from it. Road and obstacles are extracted using a modified Hough transform. Our experimental results on real images show the efficiency of our algorithm.
['Rawia Mhiri', 'Hichem Maiza', 'Stéphane Mousset', 'Khaled Taouil', 'Pascal Vasseur', 'Abdelaziz Bensrhair']
Obstacle detection using unsynchronized multi-camera network