Binocular matching constraints from motion
Structure from motion and structure from stereo are two vision cues for achieving 3D reconstruction. The two cues have complementary strengths; while 3D reconstruction is accurate but correspondence establishment is difficult in the stereo cue, the reverse is true in the motion cue. This paper addresses how to combine the two cues when a stereo pair of cameras are available to capture image data for 3D reconstruction. The work is distinct in that, in contrast with the previous ones, it is not to exploit the redundancy in the image data for boosting the reconstruction accuracy, but to make the two vision cues complementary, preserving their strengths and avoiding their weaknesses. A mechanism is introduced that allows dense motion correspondences in the two separate image streams be transferred to dense binocular correspondences across the image streams, so that 3D can be reconstructed from the latter and accurate reconstruction is possible even with short motions of the stereo rig. Both the stereo correspondences and the motion of the stereo rig are assumed to be unknown in this work. Experiments involving real image data are presented to indicate the feasibility and robustness of the approach.
geometric matching constraints cooperative stereo-motion 3d motion estimation feature transfer 3d euclidean reconstruction 3d projective reconstruction