3D road curb extraction from image sequence for automobile parking assist system

We extract 3D curb from video sequence, using a single camera equipped with fish-eye lens and located at the front/rear of the vehicle. The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D geometry, and temporal information, one can reliably detect and localize the curbs in the 3D scene. The main underlying assumption of our model is that the road surface is flat and that the curb is approximately orthogonal to the road plane. We collected nine videos with ground truth, under day-time sunny weather condition, up to 2m range. Our experimental results compare favorably wrt the current the state-of-the-art on our database —90% precision rate in average and over 85% accuracy in curb height estimation.