Detection of three-dimensional surfaces from optic flow: the effects of noise

Previous research (Andersen, 1989) has suggested that the recovery of 3-D shape from nonsmooth optic flow (motion transparency) can be performed by segregating surfaces according to the distributions of velocities present in the flow field. Five experiments were conducted to examine this hypothesis in a surface detection paradigm and to determine the limitations of human observers to detect 3-D surfaces in the presence of noise. Two display types were examined: a flow field that simulated a surface corrugated in depth and a flow field that simulated a random volume. In addition, two types of noise were examined: a distribution of noise velocities that overlapped or did not overlap the velocity distribution that defined the surface. Corrugation frequency and surface density were also examined. Detection performance increased with decreasing corrugation frequency, decreasing noise density, and decreasing surface density. Overall, the subjects demonstrated remarkable tolerance to the presence of noise and, for some conditions, could discriminate surface from random conditions when noise density was twice the surface density. Discrimination accuracy was greater for the nonoverlapping than for the overlapping noise, providing support for an analysis based on the distribution of velocities.