Most current models of how people perceive the 3-D shape of moving objects are capable of determining shape when only a single object is present. However, in the real world we usually encounter scenes in which many objects are moving. This research will develop a new model of the perception of the shape of objects when several objects are moving in a scene. The research will study scenes in which overlapping objects cannot be distinguished in a static view, but can be distinguished when the observer or the objects are in motion. Three sets of experiments will determine the limitations of human observers in perceiving multiple moving objects. The first set of experiments will study people's ability to determine the number of objects that are moving in a complex scene. The second set of experiments will study how people identify the shapes of objects moving in a scene. The third set of experiments will study how people judge the amount of depth between objects in the scene. These results will facilitate the three-stage development of the model. The first stage will use results from the first set of experiments to derive mathematically the number of independent objects that are moving in a computer-generated scene. The second stage will use results from the second set of experiments to describe mathematically the shape of small regions of each object. The third stage will use results from the third set of experiments to specify a quantitative value of the distance between objects in a scene. An understanding of how the visual system determines the shape and depth of multiple moving objects will have important implications for the design of computer-generated displays used to train pilots, for the development of visual aids for the blind, and for the development of robotics vision systems.
