Making a Machine That Sees Like Us by Zygmunt Pizlo (English) Hardcover Book

Description: Making a Machine That Sees Like Us by Zygmunt Pizlo, Yunfeng Li, Tadamasa Sawada, Robert M. Steinman Making a Machine That Sees Like Us explains why and how our visual perceptions can provide us with an accurate representation of the world out there. Along the way, it tells the story of a machine (a computational model) built by the authors that solves the computationally difficult problem of seeing the way humans do. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description Making a Machine That Sees Like Us explains why and how our visual perceptions can provide us with an accurate representation of the external world. Along the way, it tells the story of a machine (a computational model) built by the authors that solves the computationally difficult problem of seeing the way humans do. This accomplishment required a radical paradigm shift - one that challenged preconceptions about visual perception and tested the limits ofhuman behavior-modeling for practical application.The text balances scientific sophistication and compelling storytelling, making it accessible to both technical and general readers. Onlinedemonstrations and references to the authors previously published papers detail how the machine was developed and what drove the ideas needed to make it work. The authors contextualize their new theory of shape perception by highlighting criticisms and opposing theories, offering readers a fascinating account not only of their revolutionary results, but of the scientific process that guided the way. Author Biography Zygmunt Pizlo is a professor of Psychological Sciences and of Electrical and Computer Engineering at Purdue University. He has published over 100 journal and conference papers on all aspects of vision as well as on problem-solving. In 2008, he published the first book devoted to 3D shape-perception.Yunfeng Li is a postdoctoral fellow at Purdue University. His research interests focus on applying psychophysics and mathematics to explore and model human visual perception of 3D shapes and scenes, regularization and Bayesian methods, and human and robot visual navigation.Tadamasa Sawada is a postdoctoral researcher in the Graduate Center for Vision Research at SUNY College of Optometry. He has received his Ph.D. from the Tokyo Institute of Technology in 2006 and had worked as a postdoctoral researcher at Purdue University (2006-2013) and at the Ohio State University (2013-2014). He has been studying human visual perception using psychophysical experiments as well as mathematical and computational modeling.Robert M. Steinman devoted most of his scientific career, which began in 1964, to sensory and perceptual process, heading this specialty area in the Department of Psychology at the University of Maryland in College Park until his retirement in 2008. Most of his publications, before collaborating on shape perception with Prof. Pizlo, were concerned with human eye movements. Prof. Steinman, with Prof. Azriel Rosenfeld of the Center for Automation Research at UMD, supervised Prof. Pizlos doctoraldegree in Psychology, which was awarded in 1991. Prof. Steinman has been collaborating with Prof. Pizlo in his studies of shape perception since 2000. Table of Contents Making a Machine That Sees Like Us1. How the Stage Was Set When We Began1.1 Introduction1.2 What is this book about?1.3 Analytical and Operational definitions of shape1.4 Shape constancy as a phenomenon (something you can observe)1.5 Complexity makes shape unique1.6 How would the world look if we are wrong?1.7 What had happened in the real world while we were away1.8 Perception viewed as an Inverse Problem1.9 How Bayesian inference can be used for modeling perception1.10 What it means to have a model of vision, and why we need to have one1.11 End of the beginning.2. How This All Got Started2.1 Controversy about shape constancy: 1980 - 19952.2 Events surrounding the 29th European Conference on Visual Perception (ECVP), St. Petersburg, Russia, August 20 - 25, 2006 where we first announced our paradigm shift2.3 The role of constraints in recovering the 3D shapes of polyhedral objects from line-drawings2.4 Events surrounding the 31st European Conference on Visual Perception (ECVP) Utrecht, NL, August 24 - 28, 2008, where we had our first big public confrontation2.5 Monocular 3D shape recovery of both synthetic and real objects3. Symmetry in Vision, Inside and Outside of the Laboratory3.1 Why and how approximate computations make visual analyses fast and perfect: the perception of slanted 2D mirror-symmetrical figures3.2 How human beings perceive 2D mirror-symmetry from perspective images3.3 Why 3D mirror-symmetry is more difficult than 2D symmetry3.4 Updating the Ideal Observer: how human beings perceive 3D mirror-symmetry from perspective images3.5 Important role of Generalized Cones in 3D shape perception: how human beings perceive 3D translational-symmetry from perspective images3.6 Michael Laytons contribution to symmetry in shape perception3.7 Leeuwenbergs attempt to develop a "Structural" explanation of Gestalt phenomena4. Using Symmetry Is Not Simple4.1 What is really going on? Examining the relationship between simplicity and likelihood4.2 Clearly, simplicity is better than likelihood - excluding degenerate views does not eliminate spurious 3D symmetrical interpretations4.3 What goes with what? A new kind of Correspondence Problem4.4 Everything becomes easier once symmetry is viewed as self-similarity: the first working solution of the Symmetry Correspondence Problem5. A Second View Makes 3D Shape Perception Perfect5.1 What we know about binocular vision and how we came to know it5.2 How we worked out the binocular perception of symmetrical 3D shapes5.3 How our new theory of shape perception, based on stereoacuity, accounts for old results5.4 3D movies: what they are, what they want to be, and what it costs5.5 Bayesian model of binocular shape perception5.6 Why we could claim that our model is complete6. Figure-Ground Organization, which Breaks Camouflage in Everyday Life, Permits the Veridical Recovery of a 3D Scene6.1 Estimating the orientation of the ground-plane6.2 How a coarse analysis of the positions and sizes of objects can be made6.3 How a useful top-view representation was produced6.4 Finding objects in the 2D image6.5 Extracting relevant edges, grouping them and establishing symmetry correspondence6.6 What can be done with a spatially-global map of a 3D scene?7. What Made This Possible and What Comes Next?7.1 Five Important conceptual contributions7.2 Three of our technical contributions7.3 Making our machine perceive and predict in dynamical environments7.4 Solving the Figure-Ground Organization Problem with only a single 2D image7.5 Recognizing individual objects by using a fast search of memory. Review "Written in a conversational manner, the book outlines in a step-by-step fashion the rationale for the model and some important ways in which the model differs from other contemporarycomputational approaches. Making a Machine That Sees Like Us is an important book for anyone with an interest in machine vision for it offers a bottom-up approach to object perception that incorporates a priori constraints rather than sensory data alone. No doubt the inclusion of sensory data together with the constraints is the determining factor in its success as a model of machine vision. It is written in a style that is easy to read by those who do not have much background invisual perception." --PsycCRITIQUES"This book is timely, interesting, even provocative, and well worth reading. It is especially likely to be of considerable interest to the mathematical psychology community because vision has always enjoyed a special status in the field." --Journal of Mathematical Psychology Promotional Making a Machine That Sees Like Us explains why and how our visual perceptions can provide us with an accurate representation of the world out there. Long Description Making a Machine That Sees Like Us explains why and how our visual perceptions can provide us with an accurate representation of the external world. Along the way, it tells the story of a machine (a computational model) built by the authors that solves the computationally difficult problem of seeing the way humans do. This accomplishment required a radical paradigm shift - one that challenged preconceptions about visual perception and tested the limits ofhuman behavior-modeling for practical application.The text balances scientific sophistication and compelling storytelling, making it accessible to both technical and general readers. Onlinedemonstrations and references to the authors previously published papers detail how the machine was developed and what drove the ideas needed to make it work. The authors contextualize their new theory of shape perception by highlighting criticisms and opposing theories, offering readers a fascinating account not only of their revolutionary results, but of the scientific process that guided the way. Review Text "Written in a conversational manner, the book outlines in a step-by-step fashion the rationale for the model and some important ways in which the model differs from other contemporary computational approaches. Making a Machine That Sees Like Us is an important book for anyone with an interest in machine vision for it offers a bottom-up approach to object perception that incorporates a priori constraints rather than sensory data alone. No doubt the inclusion of sensory data together with the constraints is the determining factor in its success as a model of machine vision. It is written in a style that is easy to read by those who do not have much background invisual perception." --PsycCRITIQUES"This book is timely, interesting, even provocative, and well worth reading. It is especially likely to be of considerable interest to the mathematical psychology community because vision has always enjoyed a special status in the field." --Journal of Mathematical Psychology Review Quote "Written in a conversational manner, the book outlines in a step-by-step fashion the rationale for the model and some important ways in which the model differs from other contemporary computational approaches. Making a Machine That Sees Like Us is an important book for anyone with an interest in machine vision for it offers a bottom-up approach to object perception that incorporates a priori constraints rather than sensory data alone. No doubt the inclusion of sensory data together with the constraints is the determining factor in its success as a model of machine vision. It is written in a style that is easy to read by those who do not have much background in visual perception." --PsycCRITIQUES "This book is timely, interesting, even provocative, and well worth reading. It is especially likely to be of considerable interest to the mathematical psychology community because vision has always enjoyed a special status in the field." --Journal of Mathematical Psychology Feature Selling point: Argues that visual perception needs to be studied differently than it has until nowSelling point: Written in two distinct voices: one for intuitive readers and the other for technical readersSelling point: Tells the story of a machine, created by the authors, that sees almost like humansSelling point: Interactive online demonstrations highlight key moments in the development of the authors vision machine Details ISBN0199922543 Author Robert M. Steinman Short Title MAKING A MACHINE THAT SEES LIK Language English ISBN-10 0199922543 ISBN-13 9780199922543 Media Book Format Hardcover Year 2014 Illustrations Yes DEWEY 152.14 Position Postdoctoral Fellow Place of Publication New York Country of Publication United States Affiliation Postdoctoral Fellow, Purdue University Publication Date 2014-05-29 UK Release Date 2014-05-29 AU Release Date 2014-05-29 NZ Release Date 2014-05-29 US Release Date 2014-05-29 Pages 256 Publisher Oxford University Press Inc Imprint Oxford University Press Inc Audience Postgraduate, Research & Scholarly We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:127256956;

Price: 102.94 AUD

Location: Melbourne

End Time: 2024-12-06T06:02:59.000Z

Shipping Cost: 9.69 AUD