People are able to perceive objects and boundaries successfully, despite the fact that the visual input on which that perception is based is fragmentary across both space and time. For instance, despite the fact that objects are occluded a great deal by other objects and that patterns projected on the retina change continually whenever objects or observers move, people can ordinarily detect complete boundaries and shapes. There are other cases in which people perceive boundaries in the absence of local visual information, known as illusory contours and transparency phenomena. This project will address the various cases of boundary interpolation; it will test and refine a proposed unifying theory and extend that theory from static, two-dimensional displays to the three-dimensional case and to cases in which boundaries are obtained from information conveyed by motion. The project will also investigate convergent methods to assess boundary perception, including both perceptual report and objective performance measures. This research, in addition to its implications for understanding human perception of objects, will aid in the construction of object and boundary detection methods in computer vision systems.
