Shape Perception As Bayesian Inference Of Modality Independent Part Based 3d Object Centered Shape Representations
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Author | : Derek Hoiem |
Publisher | : Morgan & Claypool Publishers |
Total Pages | : 172 |
Release | : 2011 |
Genre | : Computers |
ISBN | : 1608457281 |
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions
Author | : Emanuel Leeuwenberg |
Publisher | : Cambridge University Press |
Total Pages | : 337 |
Release | : 2013 |
Genre | : Language Arts & Disciplines |
ISBN | : 1107029600 |
A coherent and comprehensive theory of visual pattern classification with quantitative models, verifiable predictions and extensive empirical evidence.
Author | : Brian Kulis |
Publisher | : Now Pub |
Total Pages | : 92 |
Release | : 2013 |
Genre | : Computers |
ISBN | : 9781601986962 |
Metric Learning: A Review presents an overview of existing research in metric learning, including recent progress on scaling to high-dimensional feature spaces and to data sets with an extremely large number of data points. It presents as unified a framework as possible under which existing research on metric learning can be cast.
Author | : Andy Clark |
Publisher | : Oxford University Press, USA |
Total Pages | : 425 |
Release | : 2016 |
Genre | : Medical |
ISBN | : 0190217014 |
Exciting new theories in neuroscience, psychology, and artificial intelligence are revealing minds like ours as predictive minds, forever trying to guess the incoming streams of sensory stimulation before they arrive. In this up-to-the-minute treatment, philosopher and cognitive scientist Andy Clark explores new ways of thinking about perception, action, and the embodied mind.
Author | : Shuo Li |
Publisher | : Springer Science & Business Media |
Total Pages | : 441 |
Release | : 2014-01-28 |
Genre | : Technology & Engineering |
ISBN | : 3319038133 |
This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.
Author | : Jan J. Koenderink |
Publisher | : Mit Press |
Total Pages | : 699 |
Release | : 1990 |
Genre | : Computers |
ISBN | : 9780262111393 |
Solid Shape gives engineers and applied scientists access to the extensive mathematical literature on three dimensional shapes. Drawing on the author's deep and personal understanding of three-dimensional space, it adopts an intuitive visual approach designed to develop heuristic tools of real use in applied contexts.Increasing activity in such areas as computer aided design and robotics calls for sophisticated methods to characterize solid objects. A wealth of mathematical research exists that can greatly facilitate this work yet engineers have continued to "reinvent the wheel" as they grapple with problems in three dimensional geometry. Solid Shape bridges the gap that now exists between technical and modern geometry and shape theory or computer vision, offering engineers a new way to develop the intuitive feel for behavior of a system under varying situations without learning the mathematicians' formal proofs. Reliance on descriptive geometry rather than analysis and on representations most easily implemented on microcomputers reinforces this emphasis on transforming the theoretical to the practical.Chapters cover shape and space, Euclidean space, curved submanifolds, curves, local patches, global patches, applications in ecological optics, morphogenesis, shape in flux, and flux models. A final chapter on literature research and an appendix on how to draw and use diagrams invite readers to follow their own pursuits in threedimensional shape.Jan J. Koenderinck is Professor in the Department of Physics and Astronomy at Utrecht University. Solid Shape is included in the Artificial Intelligence series, edited by Patrick Winston, Michael Brady, and Daniel Bobrow
Author | : Martha E. Arterberry |
Publisher | : Oxford University Press |
Total Pages | : 393 |
Release | : 2016-04-15 |
Genre | : Psychology |
ISBN | : 0199395659 |
The developing infant can accomplish all important perceptual tasks that an adult can, albeit with less skill or precision. Through infant perception research, infant responses to experiences enable researchers to reveal perceptual competence, test hypotheses about processes, and infer neural mechanisms, and researchers are able to address age-old questions about perception and the origins of knowledge. In Development of Perception in Infancy: The Cradle of Knowledge Revisited, Martha E. Arterberry and Philip J. Kellman study the methods and data of scientific research on infant perception, introducing and analyzing topics (such as space, pattern, object, and motion perception) through philosophical, theoretical, and historical contexts. Infant perception research is placed in a philosophical context by addressing the abilities with which humans appear to be born, those that appear to emerge due to experience, and the interaction of the two. The theoretical perspective is informed by the ecological tradition, and from such a perspective the authors focus on the information available for perception, when it is used by the developing infant, the fit between infant capabilities and environmental demands, and the role of perceptual learning. Since the original publication of this book in 1998 (MIT), Arterberry and Kellman address in addition the mechanisms of change, placing the basic capacities of infants at different ages and exploring what it is that infants do with this information. Significantly, the authors feature the perceptual underpinnings of social and cognitive development, and consider two examples of atypical development - congenital cataracts and Autism Spectrum Disorder. Professionals and students alike will find this book a critical resource to understanding perception, cognitive development, social development, infancy, and developmental cognitive neuroscience, as research on the origins of perception has changed forever our conceptions of how human mental life begins.
Author | : Timothy L. Hubbard |
Publisher | : Cambridge University Press |
Total Pages | : 505 |
Release | : 2018-08-23 |
Genre | : Psychology |
ISBN | : 1107154987 |
Numerous spatial biases influence navigation, interactions, and preferences in our environment. This volume considers their influences on perception and memory.
Author | : Shimon Ullman |
Publisher | : MIT Press (MA) |
Total Pages | : 244 |
Release | : 1979-02-01 |
Genre | : Computers |
ISBN | : 9780262710114 |
This book uses the methodology of artificial intelligence to investigate the phenomena of visual motion perception: how the visual system constructs descriptions of the environment in terms of objects, their three-dimensional shape, and their motion through space, on the basis of the changing image that reaches the eye. The author has analyzed the computations performed in the course of visual motion analysis. Workable schemes able to perform certain tasks performed by the visual system have been constructed and used as vehicles for investigating the problems faced by the visual system and its methods for solving them.Two major problems are treated: first, the correspondence problem, which concerns the identification of image elements that represent the same object at different times, thereby maintaining the perceptual identity of the object in motion or in change. The second problem is the three-dimensional interpretation of the changing image once a correspondence has been established.The author's computational approach to visual theory makes the work unique, and it should be of interest to psychologists working in visual perception and readers interested in cognitive studies in general, as well as computer scientists interested in machine vision, theoretical neurophysiologists, and philosophers of science.
Author | : Douglas McNair |
Publisher | : Intechopen |
Total Pages | : 138 |
Release | : 2019 |
Genre | : Mathematics |
ISBN | : 1839623225 |
Bayesian networks (BN) have recently experienced increased interest and diverse applications in numerous areas, including economics, risk analysis and assets and liabilities management, AI and robotics, transportation systems planning and optimization, political science analytics, law and forensic science assessment of agency and culpability, pharmacology and pharmacogenomics, systems biology and metabolomics, psychology, and policy-making and social programs evaluation. This strong and varied response results not least from the fact that plausibilistic Bayesian models of structures and processes can be robust and stable representations of causal relationships. Additionally, BNs' amenability to incremental or longitudinal improvement through incorporating new data affords extra advantages compared to traditional frequentist statistical methods. Contributors to this volume elucidate various new developments in these aspects of BNs.