Familiarity Dominates Shape-From-Motion Signals in the Concave-to-Convex 3D illusion

Abstract

OBJECTIVE: Investigate role of top-down influences on recovering 3D shape from motion information, using objects varying in familiarity to test familiarity’s role on the tendency to perceive concave surfaces as convex. BACKGROUND: We reported (Papathomas et al, VSS 2011) that rotating hollow masks are perceived as convex faces rotating in the opposite direction, even in conditions where shape-from-motion signals have previously generated concave 3D percepts for artificial stimuli. We now test directly whether these results were dominated by object familiarity. METHODS: Experiment 1 used hollow, realistically painted, physical stimuli rotating on a turntable: (1) facial mask, (2) watermelon. Experiment 2 used four computer-generated concave stimuli: (1) Realistic human mask, using FaceGen^TM; (2) ellipsoid rendered as watermelon; (3) ellipsoid with random-dot texture; (4) ellipsoid shown by longitude and latitude gridlines. In both experiments, the center (C) of the turntable was at a fixed distance from the observer. For artificial stimuli, motion parallax signals dominate the percept (Zaidi et al, 2011). We manipulated parallax by using 6 different rotational radii (distance between C and stimulus centroid). The illusion-strength was estimated by the time reported in the illusion divided by the total time that the concave side faced the observer. RESULTS: Experiment 1: The illusion was obtained for significantly longer intervals for the face than the watermelon; illusion-strength did not vary significantly with rotational radius. Experiment 2: Illusion-strength, averaged across rotational radii, was significantly higher for the human mask (44%) and watermelon (47%) than for the random-textured (35%) or gridline (28%) ellipsoids. CONCLUSIONS: The experiments provide evidence for a top-down bias to perceive familiar objects as convex that is greater than the bias for less familiar objects. Real objects are predominantly convex, so familiarity significantly influences the recovery of 3D structure and shape from bottom-up data-driven motion signals.

Meeting abstract presented at VSS 2012