Computational Models of Visual Processing

Computational Models of Visual Processing PDF

Author: Michael Landy

Publisher: Bradford Book

Published: 1991-10-24

Total Pages: 406

ISBN-13: 9780262527989

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The more than twenty contributions in this book, all new and previously unpublished, provide an up-to-date survey of contemporary research on computational modeling of the visual system.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

Integration of Natural Language and Vision Processing

Integration of Natural Language and Vision Processing PDF

Author: Paul Mc Kevitt

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 218

ISBN-13: 9400917163

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Although there has been much progress in developing theories, models and systems in the areas of Natural Language Processing (NLP) and Vision Processing (VP) there has up to now been little progress on integrating these two subareas of Artificial Intelligence (AI). This book contains a set of edited papers on recent advances in the theories, computational models and systems of the integration of NLP and VP. The volume includes original work of notable researchers: Alex Waibel outlines multimodal interfaces including studies in speech, gesture and points; eye-gaze, lip motion and facial expression; hand writing, face recognition, face tracking and sound localization in a connectionist framework. Antony Cohen and John Gooday use spatial relations to describe visual languages. Naoguki Okada considers intentions of agents in visual environments. In addition to these studies, the volume includes many recent advances from North America, Europe and Asia demonstrating the fact that integration of Natural Language Processing and Vision is truly an international challenge.

Computational Models of Visual Processing

Computational Models of Visual Processing PDF

Author: Michael S. Landy

Publisher: MIT Press

Published: 1991

Total Pages: 420

ISBN-13: 9780262121552

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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

Integration of Natural Language and Vision Processing

Integration of Natural Language and Vision Processing PDF

Author: Paul Mc Kevitt

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 307

ISBN-13: 9401102732

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Although there has been much progress in developing theories, models and systems in the areas of Natural Language Processing (NLP) and Vision Processing (VP) there has heretofore been little progress on integrating these subareas of Artificial Intelligence (AI). This book contains a set of edited papers addressing computational models and systems for the integration of NLP and VP. The papers focus on site descriptions such as that of the large Japanese $500 million Real World Computing (RWC) project, on historical philosophical issues, on systems which have been built and which integrate the processing of visual scenes together with language about them, and on spatial relations which appear to be the key to integration. The U.S.A., Japan and the EU are well reflected, showing up the fact that integration is a truly international issue. There is no doubt that all of this will be necessary for the InformationSuperHighways of the future.

Selective Visual Attention

Selective Visual Attention PDF

Author: Liming Zhang

Publisher: John Wiley & Sons

Published: 2013-03-15

Total Pages: 344

ISBN-13: 1118060059

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Visual attention is a relatively new area of study combining a number of disciplines: artificial neural networks, artificial intelligence, vision science and psychology. The aim is to build computational models similar to human vision in order to solve tough problems for many potential applications including object recognition, unmanned vehicle navigation, and image and video coding and processing. In this book, the authors provide an up to date and highly applied introduction to the topic of visual attention, aiding researchers in creating powerful computer vision systems. Areas covered include the significance of vision research, psychology and computer vision, existing computational visual attention models, and the authors' contributions on visual attention models, and applications in various image and video processing tasks. This book is geared for graduates students and researchers in neural networks, image processing, machine learning, computer vision, and other areas of biologically inspired model building and applications. The book can also be used by practicing engineers looking for techniques involving the application of image coding, video processing, machine vision and brain-like robots to real-world systems. Other students and researchers with interdisciplinary interests will also find this book appealing. Provides a key knowledge boost to developers of image processing applications Is unique in emphasizing the practical utility of attention mechanisms Includes a number of real-world examples that readers can implement in their own work: robot navigation and object selection image and video quality assessment image and video coding Provides codes for users to apply in practical attentional models and mechanisms

Human Perception of Visual Information

Human Perception of Visual Information PDF

Author: Bogdan Ionescu

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 297

ISBN-13: 3030814653

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Recent years have witnessed important advancements in our understanding of the psychological underpinnings of subjective properties of visual information, such as aesthetics, memorability, or induced emotions. Concurrently, computational models of objective visual properties such as semantic labelling and geometric relationships have made significant breakthroughs using the latest achievements in machine learning and large-scale data collection. There has also been limited but important work exploiting these breakthroughs to improve computational modelling of subjective visual properties. The time is ripe to explore how advances in both of these fields of study can be mutually enriching and lead to further progress. This book combines perspectives from psychology and machine learning to showcase a new, unified understanding of how images and videos influence high-level visual perception - particularly interestingness, affective values and emotions, aesthetic values, memorability, novelty, complexity, visual composition and stylistic attributes, and creativity. These human-based metrics are interesting for a very broad range of current applications, ranging from content retrieval and search, storytelling, to targeted advertising, education and learning, and content filtering. Work already exists in the literature that studies the psychological aspects of these notions or investigates potential correlations between two or more of these human concepts. Attempts at building computational models capable of predicting such notions can also be found, using state-of-the-art machine learning techniques. Nevertheless their performance proves that there is still room for improvement, as the tasks are by nature highly challenging and multifaceted, requiring thought on both the psychological implications of the human concepts, as well as their translation to machines.

Computational Visual Attention Models

Computational Visual Attention Models PDF

Author: Milind S. Gide

Publisher:

Published: 2017-06-27

Total Pages: 98

ISBN-13: 9781680832808

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The human visual system has evolved to have the ability to selectively focus on the most relevant parts of a visual scene. This mechanism, referred to as visual attention, has been the focus of several neurological and psychological studies in the past few decades. These studies have inspired several computational visual attention models which have been successfully applied to problems in computer vision and robotics. Computational Visual Attention Models provides a comprehensive survey of the state-of-the-art in computational visual attention modeling with a special focus on the latest trends. By reviewing several models published since 2012, the theoretical advantages and disadvantages of each approach are discussed. In addition, existing methodologies to evaluate computational models through the use of eye-tracking data along with the visual attention performance metrics used are described. The shortcomings in existing approaches and approaches to overcome them are also covered. Finally, a subjective evaluation for benchmarking existing visual attention metrics is presented and open problems in visual attention are highlighted. This monograph provides the reader with an in-depth survey of the research conducted to date in computational visual attention models and provides the basis for further research in this exciting area.

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