The measurement and use of visual motion is a fundamental component of biological and machine vision systems that provides essential sensory information for tasks such as navigation, object manipulation and recognition. Significant advances have been made toward understanding how vision systems might solve the individual problems of detecting sudden movements, segmenting the scence into distinct objects on the basic of motion discontinuities, tracking objects of interest, recovering the three-dimensional structure and movement of object surfaces, and inferring their own movement relative to the environment. This research examines how solutions to these problems are integrated into a motion analysis that performs these functions with speed, accuracy, reliability and flexibility. Such a system must embody multiple computational strategies that combine fast and robust methods for deriving qualitative motion information with slower, accurate methods for deriving quantitative models of three- dimensional structure and motion. The approach taken in this project brings together theoretical analyses, implementation and testing of computer algorithms, and observations on human motion perception. This research will lead both to significant improvements in the performance of computer vision systems at analyzing dynamic images, and new understanding of motion analysis in the human visual system.
