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Vision in 3D Environments

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Seeing in 3D is a fundamental problem for anyorganism or device that has to operate in the real world. Answering questions such as “how far away is that?” or “can we fit through that opening?” requires perceiving and making judgments about the size of objects in three dimensions. So how do we see in three dimensions? Given a sufficientlyaccurate model of the world and its illumination, complex but accurate models exist for generating the pattern of illumination that will strike the retina or cameras of an active agent (see Foley et al., 1995). The inverse problem, howto build a three-dimensional representation from such two-dimensional patterns of light impinging on our retinas or the cameras of a robot, is considerablymore complex.

In fact, the problem of perceiving 3D shape and layout is a classic example of an ill-posed and underconstrained inverse problem. It is an underconstrained problem because a unique solution is not obtainable from the visual input. Even when two views are present (with the slightlydif fering viewpoints of each eye), the images do not necessarily contain all the information required to reconstruct the three-dimensional structure of a viewed scene. It is an illposed problem because small changes in the input can lead to significant changes in the output: that is, reconstruction is veryvulnerable to noise in the input signal. The problem of constructing the three-dimensional structure of the viewed scene is an extremelydif ficult and usuallyimpossible problem to solve uniquely. Seeing in three dimensions relies on using a range of assumptions and memories to guide the choice of solution when no unique solution is possible.

Biological and machine systems exist within a complex and changing three-dimensional world. We appear to have no difficulty understanding this world, but how do we go about forming a perceptual model of it? Centred around three key themes: depth processing and stereopsis; motion and navigation in 3D; and natural scene perception, this volume explores the latest cutting-edge research into the perception of three dimension environments. It features contributions from top researchers in the field, presenting both biological and computational perspectives. Topics covered include binocular perception; blur and perceived depth; stereoscopic motion in depth; and perceiving and remembering the shape of visual space. This unique book will provide students and researchers with an overview of ongoing research as well as perspectives on future developments in the field. Colour versions of a selection of the figures are available at www.cambridge.org/9781107001756.

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