Towards qualitative vision: motion parallax

A robot vehicle moving under visual guidance needs to compute approximate geometry of obstacles in its environment. It is unreasonable to assume that egomotion is known to the sort of precision that is available for a camera mounted on a high quality robot arm. Generally a nominal estimate for egomotion is available. One possibility is to refine this estimate using optic flow data (Harris, 1987). Alternatively, the problem can be turned on its head: what geometric information remains stable under perturbation of assumed egomotion? This question has been addressed by Koenderink and van Doom (1977), Nelson and Aloimonos (1988) and Verri et al. (1989), in the case of continuous motion fields and, in the domain of stereoscopic vision, by Weinshall (1990). Part of the answer, we claim, lies in the use of motion parallax as a geometric cue. Motion parallax, which is a relative measure of the positions of two points, can be very much more robust as a cue than the absolute position of a single point. This is true for computation of relative depth, curvature on specular surfaces and curvature on extremal boundaries.