We present a method to determine 3D motion and structure of multiple objects from two perspective views, using adaptive Hough transform. In our method, segmentation is determined based on a 3D rigidity constraint. We divide the input image into overlapping patches, and, for each sample of the translation space, we compute the rotation parameters of patches using least-squares fit.
Every patch votes for a sample in the five-dimensional parameter space.
For a patch containing multiple motions, we use a redescending M-estimator to compute rotation parameters of a dominant motion within the patch. Our method can robustly recover 3D motion parameters, reject outliers of the flow estimates, and deal with multiple moving objects present in the scene. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results. All Rights Reserved. The full text of is available to members of the IEEE Computer Society who have an online subscription and an e-account .