More than one third of the human brain is devoted to the processes of seeing - vision is after all the main way in which we gather information about the world. But human vision is a dynamic process during which the eyes continually sample the environment. Where most books on vision consider it as a passive activity, this book is unique in focusing on vision as an 'active' process. It goes beyond most accounts of vision where the focus is on seeing, to provide an integrated account of seeing AND looking. The book starts by pointing out the weaknesses in our traditional approaches to vision and the reason we need this new approach. It then gives a thorough description of basic details of the visual and oculomotor systems necessary to understand active vision. The book goes on to show how this approach can give a new perspective on visual attention, and how the approach has progressed in the areas of visual orienting, reading, visual search, scene perception and neuropsychology. Finally, the book summarises progress by showing how this approach sheds new light on the old problem of how we maintain perception of a stable visual world. Written by two leading vision scientists, this book will be valuable for vision researchers and psychology students, from undergraduate level upwards.

This book defines the emerging field of Active Perception which calls for studying perception coupled with action. It is devoted to technical problems related to the design and analysis of intelligent systems possessing perception such as the existing biological organisms and the "seeing" machines of the future. Since the appearance of the first technical results on active vision, researchers began to realize that perception -- and intelligence in general -- is not transcendental and disembodied. It is becoming clear that in the effort to build intelligent visual systems, consideration must be given to the fact that perception is intimately related to the physiology of the perceiver and the tasks that it performs. This viewpoint -- known as Purposive, Qualitative, or Animate Vision -- is the natural evolution of the principles of Active Vision. The seven chapters in this volume present various aspects of active perception, ranging from general principles and methodological matters to technical issues related to navigation, manipulation, recognition, learning, planning, reasoning, and topics related to the neurophysiology of intelligent systems.

This title focuses on vision as an active process, rather than a passive activity and provides an integrated account of seeing and looking. The authors give a thorough description of basic details of the visual and oculomotor systems necessary to understand active vision.

Active vision and perception for resource-constrained autonomous vehicles, such as small ground robots and quadrotors, are limited in their allowable algorithmic complexity and slow reaction times. For an autonomous mobile robot to safely and reliably perform a useful task or behavior, real-time visual perception that informs a controller with a fast reaction time is needed. This dissertation covers new research developments in the areas of active vision, planning, and control for directional sensors with a focus on event-cameras and RGB cameras. Event-cameras, also known as neuromorphic cameras, are biologically inspired visual sensors that measure local changes in light intensity, mitigating latency and redundant data. Several high-level active vision algorithms, interfaced with autonomous vehicle controllers, are developed for event-cameras and quantitatively compared to analogous RGB camera algorithms, in terms of both accuracy and computational cost. In particular, motion-based perception algorithms for object recognition and tracking, action recognition, and depth estimation are developed for use on a moving quadrotor tasked with reacting to the perceived environment. Novel active vision algorithms for RGB cameras are also developed in which an autonomous ground vehicle or quadrotor interact with a human target of interest using novel action recognition and tracking perception capabilities paralleled with new control methods for target following. Furthermore, a novel occlusion-avoiding path planning algorithm that is applicable to both event-cameras and RGB cameras is developed. The proposed method computes a closed-form collection of subsets of the sensor's configuration space, referred to as visibility regions, that quantify the visibility of targets subject to the sensor field of view geometry and line of sigh visibility. This method is quantitatively compared to several existing sensor path planning methods in terms of analytical computational complexity, experimental path performance, and experimental computational cost analysis. The results of this work enable active vision, perception, and planning for resource-constrained mobile robots equipped with directional sensors such as an event-camera or RGB camera.

Intelligent robotics has become the focus of extensive research activity. This effort has been motivated by the wide variety of applications that can benefit from the developments. These applications often involve mobile robots, multiple robots working and interacting in the same work area, and operations in hazardous environments like nuclear power plants. Applications in the consumer and service sectors are also attracting interest. These applications have highlighted the importance of performance, safety, reliability, and fault tolerance. This volume is a selection of papers from a NATO Advanced Study Institute held in July 1989 with a focus on active perception and robot vision. The papers deal with such issues as motion understanding, 3-D data analysis, error minimization, object and environment modeling, object detection and recognition, parallel and real-time vision, and data fusion. The paradigm underlying the papers is that robotic systems require repeated and hierarchical application of the perception-planning-action cycle. The primary focus of the papers is the perception part of the cycle. Issues related to complete implementations are also discussed.

This is at once a review and a summary of the tremendous advances that have been made in recent years on the effect of attention on visual perception. This broad-ranging volume will appeal to vision scientists as well as to those involved in using visual processes in computer animations, display design or the sensory systems of machines. Physiologists and neuroscientists interested in any aspect of sensory or motor processes will also find it very useful.