Integration of shape from shading and stereo

摘要

Stereo algorithms suffer from the lack of local surface texture due to smoothness of depth constraint, or local miss-matches in disparity estimates. Thus, most stereo methods only provide a coarse depth map which can be associated with a low pass image of the depth map. On the other hand, shape from shading algorithms generally produce better estimates of local surface areas, but some of them have problems with variable albedo and spherical surfaces. Thus, shape from shading methods produce better detailed depth information, and can be associated with the high pass image of the depth map. In order to compute a better depth map, we present a method for integrating the high frequncy information from the shape from shading and the low frequency information from stereo. The proposed algorithm is very simple, takes about 0.7 s for a 128 × 128 image on a Sun SparcStation-1, is non-iterative, and requires very little adjustment of parameters. The results obtained with a variety of synthetic and real images are discussed. The quality of depth obtained by integrating shading and stereo is compared with the ground truth (range image) using height error measure, and improvement ranging from 30 to 50% over stereo, and from 65 to 98% over shading is demonstrated.