Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene.

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 book is a dialogue between researchers who study biological visual and computer scientists and engineers who seek to build computer vision systems that actively explore the environment. By describing new and important ways to design robots analogous to biological visual systems, it provides deep insights into the problems and solutions of computer vision. The book is divided into four parts, each addressing a different aspect of exploratory or active vision in biological and machine vision systems. The chapters are written by a cross-disciplinary selection of leading researchers who study computer and biological vision. As a result, many researchers and students concerned with vision will find this an invaluable survey to this fast-moving field.