Classifying Dynamic 3-D Shape Deformations from Motion Cues

perceivers to parse retinal images object motions, object shapes, and shape deformations. We have discovered interesting details about human perception of deforming shapes from motion cues, by using movies of rigid and flexing point-light cylinders rotating simultaneously around the depth and vertical axes in perspective (Jain & Zaidi, 2011): • Observers can discern cross-sectional shapes of flexing and rigid cylinders equally well, suggesting no advantage for structure-from-motion models using rigidity assumptions. • When cylinder rotations lead to asymmetric velocity profiles, symmetric cylinders appear asymmetric, highlighting the primacy of velocity patterns in shape perception. • Inexperienced observers are generally incapable of using motion cues to detect inflation/deflation of cylinders, but this handicap can be overcome with practice equally well for rigid and flexing objects. In this study we explore the ability of observers to classify dynamic deformations from motion cues. Classifying Dynamic 3-D Shape Deformations from Motion Cues