Region-based stereo analysis for robotic applications

The authors consider the development of a practical binocular stereo approach for extracting depth information. This approach is particularly well suited for robot vision systems designed for inspection and manipulation tasks. The authors emphasize the importance of semantic content and stability of the primitive used in stereo matching and introduce the use of homogeneous regions as features in stereo matching. Considering the lower number of features and the high discrimination power of the primitive, the region-based matcher is more efficient and accurate than those using edge-based primitives. A region-based matching technique can utilize both local and global information and thus yield a more globally consistent solution. However, region-based matching processes typically yield coarse disparity maps. It is noted that it is critical that an efficient and robust stereo system utilize the most appropriate set of primitives at each state of the process. A hierarchical stereo approach that does so is proposed. Several experiments to evaluate the performance of a region-based stereo matcher and a straightforward disparity and depth generation module are described