The perceptual buildup of three-dimensional structure from motion.

We present a set of psychophysical experiments that measure the accuracy of perceived three-dimensional (3-D) structure derived from relative motion in the changing two-dimensional image. The experiments are motivated in part by a computational model proposed by Ullman (1984), called the incremental rigidity scheme, in which an accurate 3-D structure is built up incrementally, by considering images of moving objects over an extended time period. Our main conclusions are: First, the human visual system can derive an accurate model of the relative depths of moving points, even in the presence of noise in their image positions; second, the accuracy of the 3-D model improves with time, eventually reaching a plateau; and third, the 3-D structure currently perceived appears to depend on previous 3-D models. Through computer simulations, we relate the results of our psychophysical experiments with the predictions of Ullman's model.