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Examines a series of linked case studies that not only highlight moments of seeming disconnect between seeing and believing, including hoaxes, miracles, spirit paintings, manipulated photographs, and holograms, but also offer a sensory history of ways of seeing.
Advances in technology allow us to see the invisible: fetal heartbeats, seismic activity, cell mutations, virtual space. Yet in an age when experience is so intensely mediated by visual records, the centuries-old realization that knowledge gained through sight is inherently fallible takes on troubling new dimensions. This book considers the ways in which seeing, over time, has become the foundation for knowing (or at least for what we think we know). A. Joan Saab examines the scientific and socially constructed aspects of seeing in order to delineate a genealogy of visuality from the Renaissance to the present, demonstrating that what we see and how we see it are often historically situated and culturally constructed. Through a series of linked case studies that highlight moments of seeming disconnect between seeing and believing—hoaxes, miracles, spirit paintings, manipulated photographs, and holograms, to name just a few—she interrogates the relationship between “visions” and visuality. This focus on the strange and the wonderful in understanding changing notions of visions and visual culture is a compelling entry point into the increasingly urgent topic of technologically enhanced representations of reality. Accessibly written and thoroughly enlightening, Objects of Vision is a concise history of the connections between seeing and knowing that will appeal to students and teachers of visual studies and sensory, social, and cultural history.
A study on how our eyes function with our brains examines the irrational elements of physical sight and concludes that human seeing transforms both the viewer and the object being viewed.
The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world. An Unprecedented Framework for Complex Object Representation Presenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces. State-of-the-Art 3D Surface and Object Representation This well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene.
300 Astronomical Objects is a handy and comprehensive reference to the most interesting celestial objects. It takes readers on a photographic tour through the galaxy, from its solar core to its outer limits, stopping to view all the highlights and give the very latest data about the universe. Convenient sidebars with each entry provide up-to-date facts and figures on every object, including mass, magnitude, density, radius, rotation period, and surface and core temperatures. An annotated cross-section of the object enhances this information, and a full-colour photograph brings the object to life. Additional spreads bring together and explain related objects and phenomena. For example, the corresponding pages for the sun include solar power, sunspots and solar flares. Others examples include: * Mercury and its surface * The asteroid belt and 433 Eros * Jupiter and its moons, including Io, Europa and Callista * Uranus and its rings and moons, including Ariel and Titania * Outer belts and comets, such as Halley's comet, and the Deep Impact mission * Space telescopes, including the International Space Station. * 300 Astronomical Objects is a beautiful and handy reference for the amateur astronomer. AUTHOR: Jamie Wilkins has a degree in astrophysics from Cambridge University. Robert Dunn has a degree in natural sciences, specializing in physics, from Cambridge University, where he is a researcher at the Institute of Astronomy. REVIEWS: Praise for the hardcover edition: Best Books 2007, Junior High and Young Adults, Astronomy "Simply put, this book is a real gem." -- Science Books and Films "A glorious vision of the universe." -- American Reference Books Annual ILLUSTRATIONS 300 + colour illustrations, photos, sidebars and resources *
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.
Brain damage can lead to selective problems with visual perception, including visual agnosia-the inability to recognize objects even though elementary visual functions remain unimpaired. Visual Agnosia reviews all the recent records of this disorder, places these 100 or so case studies in the general context of current neuroscience, and draws relevant conclusions about the organization of normal visual processing.
This Research Topic will focus on how the visual system recognizes objects regardless of variations in the viewpoint, illumination, retinal size, background, etc. Contributors are encouraged to submit articles describing novel results, models, viewpoints, perspectives and/or methodological innovations relevant to this topic. The issues we wish to cover include, but are not limited to, perceptual invariance under one or more of the following types of image variation: • Object shape • Task • Viewpoint (from the translation and rotation of the object relative to the viewer) • Illumination, shading, and shadows • Degree of occlusion • Retinal size • Color • Surface texture • Visual context, including background clutter and crowding • Object motion (including biological motion). Examples of questions that are particularly interesting in this context include, but are not limited to: • Empirical characterizations of properties of invariance: does invariance always exist? How wide is its range and how strong is the tolerance to viewing conditions within this range? • Invariance in naïve vs. experienced subjects: Is invariance built-in or learned? How can it be learned, under which conditions and how effectively? Is it learned incidentally, or are specific task and reward structures necessary for learning? How is generalizability and transfer of learning related to the generalizability/invariance of perception? • Invariance during inference: Are there conditions (e.g. fast presentation time or otherwise resource-constrained recognition) when invariance breaks? • What are some plausible computational or neural mechanisms by which invariance could be achieved?
In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.
