Models Of The Visual System

Some of the best vision scientists in the world in their respective fields have contributed to chapters in this book. They have expertise in a wide variety of fields, including bioengineering, basic and clinical visual science, medicine, neurophysiology, optometry, and psychology. Their combined efforts have resulted in a high quality book that covers modeling and quantitative analysis of optical, neurosensory, oculomotor, perceptual and clinical systems. It includes only those techniques and models that have such fundamentally strong physiological, control system, and perceptual bases that they will serve as foundations for models and analysis techniques in the future. The book is aimed first towards seniors and beginning graduate students in biomedical engineering, neurophysiology, optometry, and psychology, who will gain a broad understanding of quantitative analysis of the visual system. In addition, it has sufficient depth in each area to be useful as an updated reference and tutorial for graduate and post-doctoral students, as well as general vision scientists.

The more than twenty contributions in this book, all new and previously unpublished, provide an up-to-date survey of contemporary research on computational modeling of the visual system. The approaches represented range from neurophysiology to psychophysics, and from retinal function to the analysis of visual cues to motion, color, texture, and depth. The contributions are linked thematically by a consistent consideration of the links between empirical data and computational models in the study of visual function. An introductory chapter by Edward Adelson and James Bergen gives a new and elegant formalization of the elements of early vision. Subsequent sections treat receptors and sampling, models of neural function, detection and discrimination, color and shading, motion and texture, and 3D shape. Each section is introduced by a brief topical review and summary. ContributorsEdward H. Adelson, Albert J. Ahumada, Jr., James R. Bergen, David G. Birch, David H. Brainard, Heinrich H. Bülthoff, Charles Chubb, Nancy J. Coletta, Michael D'Zmura, John P. Frisby, Norma Graham, Norberto M. Grzywacz, P. William Haake, Michael J. Hawken, David J. Heeger, Donald C. Hood, Elizabeth B. Johnston, Daniel Kersten, Michael S. Landy, Peter Lennie, J. Stephen Mansfield, J. Anthony Movshon, Jacob Nachmias, Andrew J. Parker, Denis G. Pelli, Stephen B. Pollard, R. Clay Reid, Robert Shapley, Carlo L. M. Tiana, Brian A. Wandell, Andrew B. Watson, David R. Williams, Hugh R. Wilson, Yuede. Yang, Alan L. Yuille

The research and exploitation of optoelectronic properties in the industrial branch of electronics is becoming more popular each day due to the important role they play in the development of a large variety of sensors, devices, and systems for identifying, measuring, and constructing. While optoelectronics study the applications of electronic devices that source, detect, and transform light, machine vision generates and detects light in order to provide imaging-based automatic inspections and analysis for such applications as automatic object and environmental inspection, process control, and robot/mobile machine guidance in industry. Machine vision is less efficient without optoelectronics, and thus, it is important to investigate the theoretical approaches to different optoelectronic devices available for machine vision as well as current scanning technologies. Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications. The book covers topics such as the design, fabrication, and implementation of sensors and devices as well as the development viewpoint of optoelectronic systems and artificial vision techniques using optoelectronic devices. The interaction and informational communication between all these mentioned devices in the complex solution of the same task is the subject of modern challenges in Industry 4.0. Thus, this book supports engineers, technology developers, academicians, researchers, and students who seek machine vision techniques for detection, measurement, and 3D reconstruction.

This volume, with chapters by leading researchers in the field, is devoted to early vision and attention, that is, to the first stages of visual information processing. This state-of-the-art look at biological neural networks spans the many subfields, such as computational and experimental neuroscience; anatomy and physiology; visual information processing and scene segmentation; perception at illusory contours; control of visual attention; and paradigms for computing with spiking neurons.

This comprehensive guide to current research captures the first wave of studies in the field, with fifty-nine chapters by leading scholars that demonstrate the usefulness of mouse models as a bridge between experimental and clinical research. The opening chapters introduce the mouse as a species and research model, discussing such topics as the mouse's evolutionary history and the mammalian visual system. Subsequent sections explore more specialized subjects, considering optics, psychophysics, and the visual behaviors of mice; the organization of the adult mouse eye and central visual system; the development of the mouse eye (including comparisons to human development); the development and plasticity of retinal projections and visuotopic maps; mouse models for human eye disease (including glaucoma and cataracts); and the application of advanced genomic technologies (including gene therapy and genetic knockouts) to the mouse visual system. Readers of this reference will see th.