Determination of Egomotion and Environmental Layout From Noisy Time-Varying Image Velocity In Binocular Image Sequences

We address the problem of interpreting time-varying image velocity fields generated by a moving binocular observer viewing a stationary environment under perspective projection to obtain 3-D information about the absolute motion of the observer (egomotion) and the absolute depth of environmental surface points. We conduct a numerical study of our algorithm (which involves solving nonlinear systems of equations) for best, random and worst case image velocity error. As well, we investigate how good the initial guess for the nonlinear system of equations has to be. Other results include the presence of multiple solutions in time, how the algorithm performs when the underlying assumptions it is based on are violated and the effect of varying the spatial extent of the image points used, of varying the spatial baseline (separation of the left and right cameras) and of varying the temporal extents of the image points used (effectively varying the temporal baselines). As well, we investigate the use of convergent/divergent as opposed to parallel stereo camera setups.