We address the problem of motion recovery for a head-eye system from stereo image sequences. Two types of motions, the translation of the vehicle and the panning motion of the head, are considered. We show how these motions and the depth map of the scene can be estimated directly from the measurements of image gradients and time derivatives in a sequence of stereo images. There is no need to estimate image motion, track a scene feature over time, or establish point correspondences in a stereo image pair. We present the results of various experiments with real scenes.

The problem of motion recovery for a head-eye system from stereo image sequences is addressed. Two types of motions, the translation of the vehicle and the panning motion of the head, are considered. It is shown how these motions and the depth map can be estimated directly from the measurements of image gradients and time derivatives. There is no need to estimate image motion, track a scene feature over time, or establish point correspondences in a stereo image pair. The results of various experiments with real scenes are presented.>

Using a stereo vision system, the authors show how the translational motion and scene structure can be recovered directly from image gradients and time derivatives. There is no need to estimate or establish correspondences between features across images. The direction of motion is recovered using a procedure which involves minimizing the sum of the squared error of a linear constraint equation over the entire image. The magnitude of the motion is estimated from the stereo disparity. The scene structure is recovered in the form of a depth map using the recovered motion, image gradients, and time derivatives. Experimental results using real images are presented.>