A hierarchical approach for obtaining structure from two-frame optical flow

A hierarchical iterative algorithm is proposed for extracting structure from two-frame optical flow. The algorithm exploits two facts: one is that in many applications, such as face and gesture recognition, the depth variation of the visible surface of an object in a scene is small compared to the distance between the optical center and the object; the other is that the time aliasing problem is alleviated at the coarse level for any two-frame optical flow estimate so that the estimate tends to be more accurate. A hierarchical representation for the relationship between the optical flow, depth, and the motion parameters is derived, and the resulting non-linear system is iteratively solved through two linear subsystems. At the coarsest level, the surface of the object tends to be flat, so that the inverse depth tends to be a constant, which is used as the initial depth map. Inverse depth and motion parameters are estimated by the two linear subsystems at each level and the results are propagated to finer levels. Error analysis and experiments using both computer-rendered images and real images demonstrate the correctness and effectiveness of our algorithm.