Image motion processing is important to machine vision systems because it can lead to the recovery of 3D structure and motion. Author Amar Mitiche offers a comprehensive mathematical treatment of this key subject in visual systems research. Mitiche examines the interpretation of point correspondences as well as the interpretation of straight line correspondences and optical flow. In addition, the author considers interpretation by knowledge-based systems and presents the relevant mathematical basis for 3D interpretation.
The organization of movement in the changing image that reaches the eye provides our visual system with a valuable source of information for analyzing the structure of our surroundings. This book examines the measurement of this movement and the use of relative movement to locate the boundaries of physical objects in the environment.
Motion processing is an essential piece of the complex brain machinery that allows us to reconstruct the 3D layout of objects in the environment, to break camouflage, to perform scene segmentation, to estimate the ego movement, and to control our action. Although motion perception and its neural basis have been a topic of intensive research and modeling the last two decades, recent experimental evidences have stressed the dynamical aspects of motion integration and segmentation. This book presents the most recent approaches that have changed our view of biological motion processing. These new experimental evidences call for new models emphasizing the collective dynamics of large population of neurons rather than the properties of separate individual filters. Chapters will stress how the dynamics of motion processing can be used as a general approach to understand the brain dynamics itself.
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.
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 constitutes the thoroughly refereed post-proceedings of the First International Workshop on Spatial Coherence for Visual Motion Analysis, 2004, held in May 2004. The eleven revised full research papers presented went through two rounds of reviewing and improvement. The papers in this volume cover a wide range in the field of motion analysis that is a central problem in computer vision. The workshop examined techniques for integrating spatial coherence constraints during motion analysis of image sequences.
This paper reviews a number of aspects of visual motion analysis in biological systems, from a computational perspective. We illustrate the kinds of insights that have been gained through computational studies and how those observations can be integrated with experimental studies from psychology and the neurosciences, to understand the particular computations used by biological systems to analyze motion. The particular areas of motion analysis that we discuss include early motion detection and measurement, the optical flow computation, motion correspondence, the detection of motion discontinuities, and the recovery of three-dimensional structure from motion. Keywords: Image analysis, Artificial intelligence.
