Originated from a small workshop on the question of how image motion is processed under natural conditions that was held in 1997 at the Institute of Advanced Studies of the Australian National University in Canberra."--Pref.

In six parts, this book considers the extent to which computational, neural, and ecological constraints have shaped the mechanisms underlying motion vision: - Early Motion Vision - Motion Signals for Local and Global Analysis - Optical Flow Patterns - Motion Vision in Action - Neural Coding of Motion - Motion in Natural Environments Each topic is introduced by a keynote chapter which is accompanied by several companion articles. Written by an international group of experts in neurobiology, psychophysics, animal behaviour, machine vision, and robotics, the book is designed to explore as comprehensively as possible the present state of knowledge concerning the principal factors that have guided the evolution of motion vision.

This comprehensive book deals with motion estimation for autonomous systems from a biological, algorithmic and digital perspective. An algorithm, which is based on the optical flow constraint equation, is described in detail.

International Series of Monographs in Experimental Psychology, Volume 16: Aspects of Motion Perception details the fundamental concepts of the visual system perception of motion. The text first details the various findings about illusory and veridical motions along with the theories conceptualized from those findings. Next, the selection covers the research that studies the reliability and validity of the theories about motion perception. The book also discusses the importance of two-component model of motion perception. The last chapter covers the characteristics of the status of perceptual experiences. The book will be of great use to behavioral scientists and biologists. Ophthalmologists will also benefit from the text.

Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception. This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.

This book on autonomous road-following vehicles brings together twenty years of innovation in the field. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques.