EYE MOVEMENTS IN THE PERCEPTION OF DEPTH FROM MOTION

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The perception of depth from motion is perhaps the important aspect of visual processing. Monocular cues to depth are all easily deceived, and binocular stereopsis is not available to monocular observers or animals with laterally places eyes. However, depth from motion may produce either ambiguous depth assignments (e.g., kinetic depth effect-KDE) or unambiguous depth percepts in the case of motion parallax even though the retinal information may be the same in the two cases. What is it that makes depth from motion parallax unambiguous? While information about the direction of observer head movement appears necessary, current research shows that the visual system actually uses a slow eye movement signal for this purpose. This project will study the mechanism by which the visual system accomplishes this task. Psychophysical experiments will use a computer system capable of integrating information from a linear head-tracking system and an infra-red eye-tracking system so that both head and eye position can be monitored. This system can also present stereoscopic versions of the motion parallax displays (using ferroelectric shutter system) so that binocular stereopsis can be used as a control to which depth from motion parallax is compared. Experiments will determine the utility of OKR or pursuit eye movements in the perception of depth from motion, including previously ambiguous conditions such as KDE. Additionally, as eye movement magnitude depends on viewing distance, the role of viewing distance in motion parallax displays will be explored. Finally, if depth from motion parallax relies on slow eye movements, then patients with eye movement dysfunction due to cortical or cerebellar lesions should show problems in the perception of depth from motion parallax. The theoretical goal is to develop a single neural network model that can account for the perception of depth from motion parallax, motion perspective, kinetic depth, stereopsis and the various neural interactions between these different depth cues. The previous neural network model (Nawrot and Blake, 1991) was confined to kinetic depth, stereopsis, and their interaction. The addition of an eye movement signal would expand the scope of the model to include motion parallax and its various interactions with binocular stereopsis.