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A visible-surface can be reconstructed either from binocular disparity or motion parallax, and several previous studies have revealed the similarity of the surface properties from either type of reconstruction. In the present research, we have studied the ability for interpolation of reconstructed surfaces, that is, a gap-spanning task was conducted using both static and dynamic random dot patterns which give the same surface perception viewed binocularly and monocularly. We found that: (1) The ability for surface interpolation based on binocular disparity is more effective than that based on motion parallax; and (2) The experimental data correspond to the simulation result of a computational model is based on standard regularization theory. Based on these results, the brain mechanisms of surface reconstruction were discussed.

A Psychophysical Study of Surface Reconstructions Based on Binocular Disparity and Motion Parallax