Symmetric objects rarely produce symmetric retinal images. However, human observers have little difficulty in discriminating whether a given retinal image was produced by a symmetric or an asymmetric object. We tested perception of planar (2D) symmetric objects when the objects were slanted in depth. First, we compared performance in detecting symmetry with dotted patterns to that with polygons. Symmetry could be detected reliably with polygons, but not with dotted patterns. Second, we showed that symmetry detection is improved when the projected symmetry axis or symmetry lines (the features representing the symmetry of the pattern itself) are known to the subject, but not when the axis of rotation (the feature representing the 3D viewing direction) is known. Third, we compared performance with orthographic images and that with perspective images, and found that performance with orthographic images is better. Finally, we tested reconstruction of symmetric polygons from orthographic images. Based on these results, we propose a computational model, which measures the asymmetry of the presented polygon based on its single orthographic or perspective image. Performance of the model is similar to the performance of human subjects. |