The Dynamics Of Invariant Object And Action Recognition In The Human Visual System
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The Dynamics Of Invariant Object And Action Recognition In The Human Visual System
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Author : Leyla Isik
language : en
Publisher:
Release Date : 2015
The Dynamics Of Invariant Object And Action Recognition In The Human Visual System written by Leyla Isik and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Humans can quickly and effortlessly recognize objects, and people and their actions from complex visual inputs. Despite the ease with which the human brain solves this problem, the underlying computational steps have remained enigmatic. What makes object and action recognition challenging are identity-preserving transformations that alter the visual appearance of objects and actions, such as changes in scale, position, and viewpoint. The majority of visual neuroscience studies examining visual recognition either use physiology recordings, which provide high spatiotemporal resolution data with limited brain coverage, or functional MRI, which provides high spatial resolution data from across the brain with limited temporal resolution. High temporal resolution data from across the brain is needed to break down and understand the computational steps underlying invariant visual recognition. In this thesis I use magenetoencephalography, machine learning, and computational modeling to study invariant visual recognition. I show that a temporal association learning rule for learning invariance in hierarchical visual systems is very robust to manipulations and visual disputations that happen during development (Chapter 2). I next show that object recognition occurs very quickly, with invariance to size and position developing in stages beginning around 100ms after stimulus onset (Chapter 3), and that action recognition occurs on a similarly fast time scale, 200 ms after video onset, with this early representation being invariant to changes in actor and viewpoint (Chapter 4). Finally, I show that the same hierarchical feedforward model can explain both the object and action recognition timing results, putting this timing data in the broader context of computer vision systems and models of the brain. This work sheds light on the computational mechanisms underlying invariant object and action recognition in the brain and demonstrates the importance of using high temporal resolution data to understand neural computations.
Object Recognition In Man Monkey And Machine
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Author : Michael J. Tarr
language : en
Publisher: MIT Press
Release Date : 1999-03-15
Object Recognition In Man Monkey And Machine written by Michael J. Tarr and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-15 with Psychology categories.
The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition. These interconnected essays on three-dimensional visual object recognition present cutting-edge research by some of the most creative neuroscientific, cognitive, and computational scientists in the field. Cassandra Moore and Patrick Cavanagh take a classic demonstration, the perception of "two-tone" images, and turn it into a method for understanding the nature of object representations in terms of surfaces and the interaction between bottom-up and top-down processes. Michael J. Tarr and Isabel Gauthier use computer graphics to study whether viewpoint-dependent recognition mechanisms can generalize between exemplars of perceptually defined classes. Melvyn A. Goodale and G. Keith Humphrey use innovative psychophysical techniques to investigate dissociable aspects of visual and spatial processing in brain-injured subjects. D.I. Perrett, M.W. Oram, and E. Ashbridge combine neurophysiological single-cell data from monkeys with computational analyses for a new way of thinking about the mechanisms that mediate viewpoint-dependent object recognition and mental rotation. Shimon Ullman also addresses possible mechanisms to account for viewpoint-dependent behavior, but from the perspective of machine vision. Finally, Philippe G. Schyns synthesizes work from many areas, to provide a coherent account of how stimulus class and recognition task interact. The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition.
Invariant Recognition Of Visual Objects
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Author : Evgeniy Bart
language : en
Publisher: Frontiers E-books
Release Date :
Invariant Recognition Of Visual Objects written by Evgeniy Bart and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
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?
Object Recognition Attention And Action
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Author : Naoyuki Osaka
language : en
Publisher: Springer
Release Date : 2010-10-21
Object Recognition Attention And Action written by Naoyuki Osaka and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-21 with Medical categories.
Human object recognition is a classical topic both for philosophy and for the natural sciences. Ultimately, understanding of object recognition will be promoted by the cooperation of behavioral research, neurophysiology, and computation. This original book provides an excellent introduction to the issues that are involved. It contains chapters that address the ways in which humans and machines attend to, recognize, and act toward objects in the visual environment.
Representation And Recognition In Vision
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Author : Shimon Edelman
language : en
Publisher: MIT Press
Release Date : 1999
Representation And Recognition In Vision written by Shimon Edelman and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
Shimon Edelman bases a comprehensive approach to visual representation on the notion of correspondence between proximal (internal) and distal similarities in objects. Researchers have long sought to understand what the brain does when we see an object, what two people have in common when they see the same object, and what a "seeing" machine would need to have in common with a human visual system. Recent neurobiological and computational advances in the study of vision have now brought us close to answering these and other questions about representation. In Representation and Recognition in Vision, Shimon Edelman bases a comprehensive approach to visual representation on the notion of correspondence between proximal (internal) and distal similarities in objects. This leads to a computationally feasible and formally veridical representation of distal objects that addresses the needs of shape categorization and can be used to derive models of perceived similarity. Edelman first discusses the representational needs of various visual recognition tasks, and surveys current theories of representation in this context. He then develops a theory of representation that is related to Shepard's notion of second-order isomorphism between representations and their targets. Edelman goes beyond Shepard by specifying the conditions under which the representations can be made formally veridical. Edelman assesses his theory's performance in identification and categorization of 3D shapes and examines it in light of psychological and neurobiological data concerning the object-processing stream in primate vision. He also discusses the connections between his theory and other efforts to understand representation in the brain.
Integrating Computational And Neural Findings In Visual Object Perception
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Author : Judith C. Peters
language : en
Publisher: Frontiers Media SA
Release Date : 2016-06-29
Integrating Computational And Neural Findings In Visual Object Perception written by Judith C. Peters and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-29 with Electronic book categories.
The articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.
High Level Vision
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Author : Shimon Ullman
language : en
Publisher: MIT Press
Release Date : 2000
High Level Vision written by Shimon Ullman and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In this book, Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In particular, he examines two major problems. The first, object recognition and classification, involves recognizing objects despite large variations in appearance caused by changes in viewing position, illumination, occlusion, and object shape. The second, visual cognition, involves the extraction of shape properties and spatial relations in the course of performing visual tasks such as object manipulation, planning movements in the environment, or interpreting graphical material such as diagrams, graphs and maps. The book first takes up object recognition and develops a novel approach to the recognition of three-dimensional objects. It then studies a number of related issues in high-level vision, including object classification, scene segmentation, and visual cognition. Using computational considerations discussed throughout the book, along with psychophysical and biological data, the final chapter proposes a model for the general flow of information in the visual cortex. Understanding vision is a key problem in the brain sciences, human cognition, and artificial intelligence. Because of the interdisciplinary nature of the theories developed in this work, High-Level Vision will be of interest to readers in all three of these fields.
Action Recognition In The Visual Periphery
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Author : Laura Fademrecht
language : en
Publisher: Logos Verlag Berlin GmbH
Release Date : 2017-03-31
Action Recognition In The Visual Periphery written by Laura Fademrecht and has been published by Logos Verlag Berlin GmbH this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Science categories.
Humans are social beings that interact with others in their surroundings. In a public space, for example on a train platform, one can observe the wide array of social actions humans express in their daily lives. There are for instance people hugging each other, waving to one another or shaking hands. A large part of our social behavior consists of carrying out such social actions and the recognition of those actions facilitates our interactions with other people. Therefore, action recognition has become more and more popular as a research topic over the years. Actions do not only appear at our point of fixation but also in the peripheral visual field. The current Ph.D. thesis aims at understanding action recognition in the human central and peripheral vision. To this end, action recognition processes have been investigated under more naturalistic conditions than has been done so far. This thesis extends the knowledge about action recognition processes into more realistic scenarios and the far visual periphery. In four studies, life size action stimuli were used (I) to examine the action categorization abilities of central and peripheral vision, (II) to investigate the viewpoint-dependency of peripheral action representations, (III) to behaviorally measure the perceptive field sizes of action sensitive channels and (IV) to investigate the influence of additional actors in the visual scene on action recognition processes. The main results of the different studies can be summarized as follows. In Study I a high categorization performance for social actions throughout the visual field with a nonlinear performance decline towards the visual periphery was shown. Study II revealed a viewpoint-dependence of action recognition only in far visual periphery. In Study III large perceptive fields for action recognition were measured that decrease in size towards the periphery. And in Study IV no influence of a surrounding crowd of people on the recognition of actions in central vision and the visual periphery was shown. In sum, this thesis provides evidence that the abilities of peripheral vision have been underestimated and that peripheral vision might play a more important role in daily life than merely triggering gaze saccades to events in our environment.
The Role Of Attention In Viewpoint Invariant Object Recognition
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Author : Brian John Stankiewicz
language : en
Publisher:
Release Date : 1997
The Role Of Attention In Viewpoint Invariant Object Recognition written by Brian John Stankiewicz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Object Recognition In The Human Visual Cortex
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Author : Kalanit Grill-Spector
language : en
Publisher:
Release Date : 1999
Object Recognition In The Human Visual Cortex written by Kalanit Grill-Spector and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.