This book presents and analyses the most recent research dedicated to restoring vision in individuals who are severely impaired or blind from retinal disease or injury. It is written by the leading groups worldwide who are at the forefront of developing artificial vision. The book begins by discussing the difficulties in comparing and interpreting functional results in the area of very low vision and the principal prospects and limitations of spatial resolution with artificial tools. Further on, chapters are included by researchers who stimulate the surface or the pigment epithelial side of the retina and by experts who work on stimulating the optic nerve, the lateral geniculate body and the superficial layers of the visual cortex. Artificial Vision: A Clinical Guide collates the most recent work of key artificial vision research groups to explain in a comparable and stringent order their varying approaches, the clinical or preclinical outcomes and their achievements during the last years. Senior ophthalmic fellows and academic practitioners will find this guide to be an indispensable resource for understanding the current status of artificial vision.

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role. This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication. Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field. This state-of-the-art book brings together selected review articles and accounts of current projects from world-renowned researchers at the forefront of this exciting area. The contributions cover topics such as: Psychology of perception Image processing Computational geometry Visual knowledge representation and languages It is this truly multi-disciplinary approach that has produced successful theories and applications for the subject.

This monograph by one of the world's leading vision researchers provides a thorough, mathematically rigorous exposition of a broad and vital area in computer vision: the problems and techniques related to three-dimensional (stereo) vision and motion. The emphasis is on using geometry to solve problems in stereo and motion, with examples from navigation and object recognition. Faugeras takes up such important problems in computer vision as projective geometry, camera calibration, edge detection, stereo vision (with many examples on real images), different kinds of representations and transformations (especially 3-D rotations), uncertainty and methods of addressing it, and object representation and recognition. His theoretical account is illustrated with the results of actual working programs.Three-Dimensional Computer Vision proposes solutions to problems arising from a specific robotics scenario in which a system must perceive and act. Moving about an unknown environment, the system has to avoid static and mobile obstacles, build models of objects and places in order to be able to recognize and locate them, and characterize its own motion and that of moving objects, by providing descriptions of the corresponding three-dimensional motions. The ideas generated, however, can be used indifferent settings, resulting in a general book on computer vision that reveals the fascinating relationship of three-dimensional geometry and the imaging process.

I. ALEKSANDER Department of Electrical Engineering and Electronics BruneI University, England The three key words that appear in the title of this book need some clarification. First, how far does the word robot reach in the context of indus trial automation? There is an argument maintaining that this range is not fixed, but increases with advancing technology. The most limited definition of the robot is also the earliest. The history is worth following because it provides a convincing backdrop to the central point of this book: vision is likely to epitomize the technolo gical advance, having the greatest effect in enlarging the definition and range of activity of robots. In the mid 1950s it was foreseen that a purely mechanical arm-like device could be used to move objects between two fixed locations. This was seen to be cost-effective only if the task was to remain fixed for some time. The need to change tasks and therefore the level of programmability of the robot was a key issue in the broadening of robot activities. Robots installed in industry in the early 1960s derived their programmability from a device called apinboard. Ver tical wires were energized sequentially in time, while horizontal wires, when energized, would trigger off elementary actions in the manipulator arm. The task of reprogramming was a huge one, as pins had to be reinserted in the board, connecting steps in time with robot actions.

This interdisciplinary work brings you to the cutting edge of emerging technologies inspired by human sight, ranging from semiconductor photoreceptors based on novel organic polymers and retinomorphic processing circuitry to low-powered devices that replicate spatial and temporal processing in the brain. Moreover, it is the first work of its kind that integrates the full range of physiological, engineering, and mathematical issues and advances together in a single source.

The second edition of this successful machine vision textbook is completely updated, revised and expanded by 35% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new camera and image acquisition interfaces, 3D sensors and technologies, 3D reconstruction, 3D object recognition and state-of-the-art classification algorithms. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13.

Perceptual Organization for Artificial Vision Systems is an edited collection of invited contributions based on papers presented at The Workshop on Perceptual Organization in Computer Vision, held in Corfu, Greece, in September 1999. The theme of the workshop was `Assessing the State of the Community and Charting New Research Directions.' Perceptual organization can be defined as the ability to impose structural regularity on sensory data, so as to group sensory primitives arising from a common underlying cause. This book explores new models, theories, and algorithms for perceptual organization. Perceptual Organization for Artificial Vision Systems includes contributions by the world's leading researchers in the field. It explores new models, theories, and algorithms for perceptual organization, as well as demonstrates the means for bringing research results and theoretical principles to fruition in the construction of computer vision systems. The focus of this collection is on the design of artificial vision systems. The chapters comprise contributions from researchers in both computer vision and human vision.