Computing visual motion in the short and the long: from receptive fields to neural networks

Theoretical approaches to the study of perceptual phenomena of short-range and long-range apparent motion are discussed. Short-range motion is estimated by real-time receptive fields sensitive to velocities of image features. The design of these receptive fields follows from the concept of convected activation profiles, where shape-preserving activity waves are excited by, and ride atop, dynamic features. Long-range motion concerns the correspondence between features in disparate images, and the perceptual impletion of a path between these corresponding features. It is argued that this illusory motion is an artifact of a more general spatiotemporal grouping process. This process is realized in a dynamic nonlinear feedback neural network that is called a neural analog diffusion-enhancement layer (NADEL). Computations suggest that the NADEL can support a variety of long-range motion percepts popularized by the Gestalt psychologists. The authors illustrate (on videotape) both classes of computation in real time on the PIPE parallel computer