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Interpretation of Visual Motion: A Computational Study provides an information processing point of view to the phenomenon of visual motion. This book discusses the computational theory formulated for recovering the scene from monocular visual motion, determining the local geometry and rigid body motion of surfaces from spatio-temporal parameters of visual motion. This compilation also provides a theoretical and computational framework for future research on visual motion, both in human vision and machine vision areas. Other topics include the computation of image flow from intensity derivatives, instantaneous image flow due to rigid motion, time and space-time derivatives of image flow, and estimation of maximum absolute error. This publication is recommended for professionals and non-specialists intending to acquire knowledge of visual motion.
This book uses the methodology of artificial intelligence to investigate the phenomena of visual motion perception: how the visual system constructs descriptions of the environment in terms of objects, their three-dimensional shape, and their motion through space, on the basis of the changing image that reaches the eye. The author has analyzed the computations performed in the course of visual motion analysis. Workable schemes able to perform certain tasks performed by the visual system have been constructed and used as vehicles for investigating the problems faced by the visual system and its methods for solving them.Two major problems are treated: first, the correspondence problem, which concerns the identification of image elements that represent the same object at different times, thereby maintaining the perceptual identity of the object in motion or in change. The second problem is the three-dimensional interpretation of the changing image once a correspondence has been established.The author's computational approach to visual theory makes the work unique, and it should be of interest to psychologists working in visual perception and readers interested in cognitive studies in general, as well as computer scientists interested in machine vision, theoretical neurophysiologists, and philosophers of science.
This book describes experimental advances made in the interpretation of visual motion over the last few years that have moved researchers closer to emulating the way in which we recover information about the surrounding world.
Designed for students, scientists and engineers interested in learning about the core ideas of vision science, this volume brings together the broad range of data and theory accumulated in this field.
The brain's ability to detect movement within the retinal image is crucial not only for determining the trajectories of moving objects, but also for identifying and interpreting image motion resulting from eye and head movements. This book summarizes our knowledge of how information about image motion is encoded in the brain. Key Features * Valuable reference source for those involved in the rapidly expanding area of motion perception * Strong emphasis on integration of physiological, computation, and psychophysical approaches * Topics include: * Principles of local motion detection * Inputs to local motion detectors * Integration of motion signals * Higher-order interpretation of motion * Motion detection and eye movements
Motion perception lies at the heart of the scientific study of vision. The motion aftereffect (MAE) is the appearance of directional movement in a stationary object or scene after the viewer has been exposed to viusal motion in the opposite direction. For example, after one has looked at a waterfall for a period of time, the scene beside the waterfall may appear to move upward when one's gaze is transfered to it. Although the phenomenon seems simple, research has revealed copmlexities in the underlying mechanisms, and offered general lessons about how the brain processes visual information. In the 1990s alone, more than 200 papers have been published on MAE, largely inspired by improved techniques for examining brain electrophysiology and by emerging new theories of motion perception.
The Senses: A Comprehensive Reference, Second Edition, Seven Volume Set is a comprehensive reference work covering the range of topics that constitute current knowledge of the neural mechanisms underlying the different senses. This important work provides the most up-to-date, cutting-edge, comprehensive reference combining volumes on all major sensory modalities in one set. Offering 264 chapters from a distinguished team of international experts, The Senses lays out current knowledge on the anatomy, physiology, and molecular biology of sensory organs, in a collection of comprehensive chapters spanning 4 volumes. Topics covered include the perception, psychophysics, and higher order processing of sensory information, as well as disorders and new diagnostic and treatment methods. Written for a wide audience, this reference work provides students, scholars, medical doctors, as well as anyone interested in neuroscience, a comprehensive overview of the knowledge accumulated on the function of sense organs, sensory systems, and how the brain processes sensory input. As with the first edition, contributions from leading scholars from around the world will ensure The Senses offers a truly international portrait of sensory physiology. The set is the definitive reference on sensory neuroscience and provides the ultimate entry point into the review and original literature in Sensory Neuroscience enabling students and scientists to delve into the subject and deepen their knowledge. All-inclusive coverage of topics: updated edition offers readers the only current reference available covering neurobiology, physiology, anatomy, and molecular biology of sense organs and the processing of sensory information in the brain Authoritative content: world-leading contributors provide readers with a reputable, dynamic and authoritative account of the topics under discussion Comprehensive-style content: in-depth, complex coverage of topics offers students at upper undergraduate level and above full insight into topics under discussion
Computer vision aims to detect and reconstruct features of surfaces from the images produced by cameras, in some way mimicking the way in which humans reconstruct features of the world around them by using their eyes. In this book the authors describe research in computer vision aimed at recovering the 3D shape of surfaces from image sequences of their 'outlines'. They provide all the necessary background in differential geometry (assuming knowledge of elementary algebra and calculus) and in the analysis of visual motion, emphasising intuitive visual understanding of the geometric techniques with computer-generated illustrations. They also give a thorough introduction to the mathematical techniques and the details of the implementations and apply the methods to data from real images using the most current techniques.
Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions. David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This MIT Press edition makes Marr's influential work available to a new generation of students and scientists. In Marr's framework, the process of vision constructs a set of representations, starting from a description of the input image and culminating with a description of three-dimensional objects in the surrounding environment. A central theme, and one that has had far-reaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis—in Marr's framework, the computational level, the algorithmic level, and the hardware implementation level. Now, thirty years later, the main problems that occupied Marr remain fundamental open problems in the study of perception. Vision provides inspiration for the continuing efforts to integrate knowledge from cognition and computation to understand vision and the brain.