Abstract
An algorithm for fusing monocular and stereo cues to get robust estimates of both motion and structure is presented. The authors' algorithm assumes the motion to be along a smooth trajectory and the sequence of images to be dense. The algorithm starts by calculating the instantaneous FOE (focus of expansion). Knowing the FOE, a MAP estimate of the displacement at each pixel and an associated confidence measure are calculated. Using the displacement estimates, a relative depth map is calculated from one of the two frame sequences. By calculating the disparities at some feature points and using information about their relative depths, the instantaneous component of velocity in the direction perpendicular to the image plane (the Z direction) is computed. Using this information, a depth map is calculated; this depth map is then used to derive a prior probability distribution for disparity that is used in matching the two frames of the stereo pairs. This method is used to estimate the disparity of each pixel independently. Experimental results on a real image sequence are given.< >