Robust depth extraction for mobile robots

Abstract
Stereoscopic techniques for recovering depth in scenes are computationally intensive and difficult to specify sufficiently well to ensure that optimal solutions are obtained in any given situation. Apparent motion cues are a far richer and more easily exploitable source of information on depth, but computing depth from motion in spatio-temporal image sequences has many pit-falls associated with it. We show that many of these can be avoided by simultaneous capture of two or more views of the scene, projected onto a single CCD sensor, using angled mirrors. The resulting fixed-camera ranging device is immune to camera vibration and motion as well as to changes in ambient illumination that occur during image capture. A 1-D, generalized gradient scheme is used to compute the apparent image motion induced by objects in the scene and hence the range to the corresponding objects. Furthermore, the fixed camera configuration enables the shape and size of the viewing filter to be preselected to optimize performance and maximize range resolution.