Every object in the world has a physical size which is intrinsic to how we interact with it: we pick up small objects like coins with our fingers, we throw footballs and swing tennis rackets, we orient our body to bigger objects like chairs and tables and we navigate with respect to landmarks like fountains and buildings. Here I argue that the size of objects in the world is a basic property of object representation with both behavioral and neural consequences. Specifically, I suggest that objects have a canonical visual size based on their real-world size (Chapter 2), and that we automatically access real-world size information when we recognize an object (Chapter 3). Further, I present evidence that there are neural consequences of realworld size for the large-scale organization of object knowledge in ventral visual cortex (Chapter 4). Specifically, there are regions with differential selectivity for big and small objects, that span from along the dorsal and lateral surfaces of occipito-temporal cortex in a mirrored organization. Finally, I suggest that the empirical findings can be coherently explained by thinking about the experience of an observer situated in a three-dimensional world. This work provides testable predictions about retinal size biases in visual experience, and an approach in which to understand the neural representation of any object in the world.

One remarkable ability of the human brain is to process large amounts of information about our surroundings to allow us to interact effectively with them. In everyday life, the most common way to interact with objects is by reaching, grasping, lifting and manipulating them. Although these may sound like simple tasks, the perceptual properties of the target object, such as its location, size, shape, and orientation all need to be processed in order to set the movement parameters that allow an accurate reach-to-grasp-to lift movement. Several brain areas work in concert to process this outstanding amount of visual information and drive the execution of a motor plan in just a few hundred milliseconds. How are these processes orchestrated? In developing this type of comprehensive knowledge about the interactions between objects perception and goal-directed actions, we have a window into the mechanisms underlying the functioning of the visuo-motor system. With this research topic we aim to further understand the neural mechanisms that mediate our interactions with the world. Therefore, we particularly encourage submission of papers that attempt to relate such findings to real-world situations by investigating behavioural and neural correlates of information processing related to eye-hand coordination and visually-guided actions, including reaching, grasping, and lifting movements. This topic welcomes submissions of original research using any relevant techniques and methods, from behavioural kinematics/kinetics, to neuroimaging and transcranial magnetic stimulation (TMS), as well as neuropsychological studies.

A comprehensive review of contemporary research in the vision sciences, reflecting the rapid advances of recent years. Visual science is the model system for neuroscience, its findings relevant to all other areas. This essential reference to contemporary visual neuroscience covers the extraordinary range of the field today, from molecules and cell assemblies to systems and therapies. It provides a state-of-the art companion to the earlier book The Visual Neurosciences (MIT Press, 2003). This volume covers the dramatic advances made in the last decade, offering new topics, new authors, and new chapters. The New Visual Neurosciences assembles groundbreaking research, written by international authorities. Many of the 112 chapters treat seminal topics not included in the earlier book. These new topics include retinal feature detection; cortical connectomics; new approaches to mid-level vision and spatiotemporal perception; the latest understanding of how multimodal integration contributes to visual perception; new theoretical work on the role of neural oscillations in information processing; and new molecular and genetic techniques for understanding visual system development. An entirely new section covers invertebrate vision, reflecting the importance of this research in understanding fundamental principles of visual processing. Another new section treats translational visual neuroscience, covering recent progress in novel treatment modalities for optic nerve disorders, macular degeneration, and retinal cell replacement. The New Visual Neurosciences is an indispensable reference for students, teachers, researchers, clinicians, and anyone interested in contemporary neuroscience. Associate Editors Marie Burns, Joy Geng, Mark Goldman, James Handa, Andrew Ishida, George R. Mangun, Kimberley McAllister, Bruno Olshausen, Gregg Recanzone, Mandyam Srinivasan, W.Martin Usrey, Michael Webster, David Whitney Sections Retinal Mechanisms and Processes Organization of Visual Pathways Subcortical Processing Processing in Primary Visual Cortex Brightness and Color Pattern, Surface, and Shape Objects and Scenes Time, Motion, and Depth Eye Movements Cortical Mechanisms of Attention, Cognition, and Multimodal Integration Invertebrate Vision Theoretical Perspectives Molecular and Developmental Processes Translational Visual Neuroscience

First published in 1995, this book presents a model for understanding the visual processing underlying perception and action, proposing a broad distinction within the brain between two kinds of vision: conscious perception and unconscious 'online' vision.

Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.

When it comes to electronics, demand grows as technology shrinks. From consumer and industrial markets to military and aerospace applications, the call is for more functionality in smaller and smaller devices. Culled from the second edition of the best-selling Electronics Handbook, Microelectronics, Second Edition presents a summary of the current state of microelectronics and its innovative directions. This book focuses on the materials, devices, and applications of microelectronics technology. It details the IC design process and VLSI circuits, including gate arrays, programmable logic devices and arrays, parasitic capacitance, and transmission line delays. Coverage ranges from thermal properties and semiconductor materials to MOSFETs, digital logic families, memory devices, microprocessors, digital-to-analog and analog-to-digital converters, digital filters, and multichip module technology. Expert contributors discuss applications in machine vision, ad hoc networks, printing technologies, and data and optical storage systems. The book also includes defining terms, references, and suggestions for further reading. This edition features two new sections on fundamental properties and semiconductor devices. With updated material and references in every chapter, Microelectronics, Second Edition is an essential reference for work with microelectronics, electronics, circuits, systems, semiconductors, logic design, and microprocessors.

Cutting-edge research on the visual cognition of scenes, covering issues that include spatial vision, context, emotion, attention, memory, and neural mechanisms underlying scene representation. For many years, researchers have studied visual recognition with objects—single, clean, clear, and isolated objects, presented to subjects at the center of the screen. In our real environment, however, objects do not appear so neatly. Our visual world is a stimulating scenery mess; fragments, colors, occlusions, motions, eye movements, context, and distraction all affect perception. In this volume, pioneering researchers address the visual cognition of scenes from neuroimaging, psychology, modeling, electrophysiology, and computer vision perspectives. Building on past research—and accepting the challenge of applying what we have learned from the study of object recognition to the visual cognition of scenes—these leading scholars consider issues of spatial vision, context, rapid perception, emotion, attention, memory, and the neural mechanisms underlying scene representation. Taken together, their contributions offer a snapshot of our current knowledge of how we understand scenes and the visual world around us. Contributors Elissa M. Aminoff, Moshe Bar, Margaret Bradley, Daniel I. Brooks, Marvin M. Chun, Ritendra Datta, Russell A. Epstein, Michèle Fabre-Thorpe, Elena Fedorovskaya, Jack L. Gallant, Helene Intraub, Dhiraj Joshi, Kestutis Kveraga, Peter J. Lang, Jia Li Xin Lu, Jiebo Luo, Quang-Tuan Luong, George L. Malcolm, Shahin Nasr, Soojin Park, Mary C. Potter, Reza Rajimehr, Dean Sabatinelli, Philippe G. Schyns, David L. Sheinberg, Heida Maria Sigurdardottir, Dustin Stansbury, Simon Thorpe, Roger Tootell, James Z. Wang

Create Genuine Visual Realism in Computer Graphics Digital Representations of the Real World: How to Capture, Model, and Render Visual Reality explains how to portray visual worlds with a high degree of realism using the latest video acquisition technology, computer graphics methods, and computer vision algorithms. It explores the integration of ne

The locus of concreteness effects in memory for verbal materials has been described here in terms of the processing of shared and distinctive information. This theoretical view is consistent with a variety of findings previously taken as support for dual coding, insofar as both verbal and perceptual information may be involved in comprehending high-imagery sentences and in learning lists of concrete words. But going beyond previous accounts of imagery, this view also can provide explanations for several findings that appear contradictory to the thesis that concrete and abstract materials differ in the form of their storage in long-term memory. Although this does not rule out a role for imagery in list learning or text comprehension, it is clear that the complex processes involved in comprehension and memory for language go beyond mechanisms supplied by a theory based on the availability of modality-specific mental representations. The task now is to determine the viability of the theory in other domains. Several domains of imagery research presented at EWIC provided fertile ground for evaluating my theoretical viewpoint. Although not all provide a basis for distinguishing representational theories of imagery from the imagery as process view, there are data in several areas that are more consistent with the latter than the former. In other cases, there are at least potential sources of evidence that would allow such a distinction.

This book provides an introduction to HCI and usability aspects of Geographical Information Systems and Science. Its aim is to introduce the principles of Human-Computer Interaction (HCI); to discuss the special usability aspects of GIS which designers and developers need to take into account when developing such systems; and to offer a set of tried and tested frameworks, matrices and techniques that can be used within GIS projects. Geographical Information Systems and other applications of computerised mapping have gained popularity in recent years. Today, computer-based maps are common on the World Wide Web, mobile phones, satellite navigation systems and in various desktop computing packages. The more sophisticated packages that allow the manipulation and analysis of geographical information are used in location decisions of new businesses, for public service delivery for planning decisions by local and central government. Many more applications exist and some estimate the number of people across the world that are using GIS in their daily work at several millions. However, many applications of GIS are hard to learn and to master. This is understandable, as until quite recently, the main focus of software vendors in the area of GIS was on the delivery of basic functionality and development of methods to present and manipulate geographical information using the available computing resources. As a result, little attention was paid to usability aspects of GIS. This is evident in many public and private systems where the terminology, conceptual design and structure are all centred around the engineering of GIS and not on the needs and concepts that are familiar to the user. This book covers a range of topics from the cognitive models of geographical representation, to interface design. It will provide the reader with frameworks and techniques that can be used and description of case studies in which these techniques have been used for computer mapping application.