Key points are not available for this paper at this time.
Scene flow is the 3D motion field of points in the world. Given N (N>1) image sequences gathered with a N-eye stereo camera or N calibrated cameras, we present a novel system which integrates 3D scene flow and structure recovery in order to complement each other's performance. We do not assume rigidity of the scene motion, thus allowing for non-rigid motion in the scene. In our work, images are segmented into small regions. We assume that each small region is undergoing similar motion, represented by a 3D affine model. Nonlinear motion model fitting based on both optical flow constraints and stereo constraints is then carried over each image region in order to simultaneously estimate 3D motion correspondences and structure. To ensure the robustness, several regularization constraints are also introduced. A recursive algorithm is designed to incorporate the local and regularization constraints. Experimental results on both synthetic and real data demonstrate the effectiveness of our integrated 3D motion and structure analysis scheme.
Zhang et al. (Thu,) studied this question.