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Author: Kestutis Kveraga Publisher: MIT Press ISBN: 0262027852 Category : Science Languages : en Pages : 339
Book Description
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
Author: Kestutis Kveraga Publisher: MIT Press ISBN: 0262027852 Category : Science Languages : en Pages : 339
Book Description
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
Author: G. Underwood Publisher: Elsevier ISBN: 0080506232 Category : Psychology Languages : en Pages : 481
Book Description
The distinguished contributors to this volume have been set the problem of describing how we know where to move our eyes. There is a great deal of current interest in the use of eye movement recordings to investigate various mental processes. The common theme is that variations in eye movements indicate variations in the processing of what is being perceived, whether in reading, driving or scene perception. However, a number of problems of interpretation are now emerging, and this edited volume sets out to address these problems. The book investigates controversies concerning the variations in eye movements associated with reading ability, concerning the extent to which text is used by the guidance mechanism while reading, concerning the relationship between eye movements and the control of other body movements, the relationship between what is inspected and what is perceived, and concerning the role of visual control attention in the acquisition of complex perceptual-motor skills, in addition to the nature of the guidance mechanism itself. The origins of the volume are in discussions held at a meeting of the European Society for Cognitive Psychology (ESCOP) that was held in Wurzburg in September 1996. The discussions concerned the landing effect in reading, an effect, that if substantiated, would provide evidence of the use of parafoveal information in eye guidance, and these discussions were explored in more detail at a small meeting in Chamonix, in February 1997. Many of the contributors to this volume were present at the meeting, but the arguments were not resolved in Chamonix either. Other leaders in the field were invited to contribute to the discussion, and this volume is the product. The argument remains unresolved, but the problem is certainly clearer.
Author: Michael Ying Yang Publisher: Academic Press ISBN: 0128173599 Category : Technology & Engineering Languages : en Pages : 424
Book Description
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Author: James Enyeart Publisher: Arena Editions ISBN: Category : American literature Languages : en Pages : 340
Book Description
Featuring a multi-faceted collection of images and words, this book is a lavishly produced companion to a major traveling exhibition documenting America just before the 21st century. 162 photos, 80 in color.
Author: Kestutis Kveraga
Author: Kestutis Kveraga
Author: G. Underwood
Author: Frances Taylor Patterson
Author: Michael Ying Yang
Author: James Enyeart
Author: Herbert Couchman McKay
Author: Frederic Fysh
Author: Edward Hammond Clarke
Author: Arthur Winfield Thomas
Author: William Shakespeare