[Human efficiency for symmetry detection on 3D bumpy surfaces].

Based on the ideal observer analysis, we investigated sampling properties of image information used by human visual system, for symmetrical pattern discrimination on 3D bumpy surface. There were three models of ideal observer (IO) to perform the task: 2D-IO using 2D projection image (i.e., retinal image), 2.5D-IO using image transformed to canonical view, and 3D-IO using recovered pattern image of 2D plane. We measured discrimination thresholds on the task for each IO model and subjects, and calculated human statistical efficiency relative to each ideal observer. The results indicated for the detection of a diagonal symmetry in the bumpy surface that human performance was similar to 3D-IO. This implies that human observers use the structure of the bumpy surface to detect the diagonal symmetry.