Richard Szeliski – författare & böcker

Computer Vision

Algorithms and Applications

Häftad, Engelska, 2023

652 kr

Skickas inom 10-15 vardagar

Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projectsIncludes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decadeProvides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and softwareSuitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Bayesian Modeling of Uncertainty in Low-Level Vision

AvRichard Szeliski

Inbunden, Engelska, 1989

1 112 kr

Skickas inom 10-15 vardagar

Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain or inaccurate, and the problems of recovering scene information from images are often ill-posed or underconstrained. This research monograph, which is based on Richard Szeliski's Ph.D. dissertation at Carnegie Mellon University, presents a Bayesian model for representing and processing uncertainty in low level vision. Recently, probabilistic models have been proposed and used in vision. Sze liski's method has a few distinguishing features that make this monograph im portant and attractive. First, he presents a systematic Bayesian probabilistic estimation framework in which we can define and compute the prior model, the sensor model, and the posterior model. Second, his method represents and computes explicitly not only the best estimates but also the level of uncertainty of those estimates using second order statistics, i.e., the variance and covariance. Third, the algorithms developed are computationally tractable for dense fields, such as depth maps constructed from stereo or range finder data, rather than just sparse data sets. Finally, Szeliski demonstrates successful applications of the method to several real world problems, including the generation of fractal surfaces, motion estimation without correspondence using sparse range data, and incremental depth from motion.

Del 79 - Springer International Series in Engineering and Computer Science

Bayesian Modeling of Uncertainty in Low-Level Vision

AvRichard Szeliski

Häftad, Engelska, 2011

1 082 kr

Skickas inom 10-15 vardagar

Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain or inaccurate, and the problems of recovering scene information from images are often ill-posed or underconstrained. This research monograph, which is based on Richard Szeliski's Ph.D. dissertation at Carnegie Mellon University, presents a Bayesian model for representing and processing uncertainty in low level vision. Recently, probabilistic models have been proposed and used in vision. Sze liski's method has a few distinguishing features that make this monograph im portant and attractive. First, he presents a systematic Bayesian probabilistic estimation framework in which we can define and compute the prior model, the sensor model, and the posterior model. Second, his method represents and computes explicitly not only the best estimates but also the level of uncertainty of those estimates using second order statistics, i.e., the variance and covariance. Third, the algorithms developed are computationally tractable for dense fields, such as depth maps constructed from stereo or range finder data, rather than just sparse data sets. Finally, Szeliski demonstrates successful applications of the method to several real world problems, including the generation of fractal surfaces, motion estimation without correspondence using sparse range data, and incremental depth from motion.

Bayesian Modeling of Uncertainty in Low-Level Vision

AvRichard Szeliski

E-bok

PDF, Engelska, 2012

1 367 kr

Läs direkt efter köp

Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain or inaccurate, and the problems of recovering scene information from images are often ill-posed or underconstrained. This research monograph, which is based on Richard Szeliski''s Ph.D. dissertation at Carnegie Mellon University, presents a Bayesian model for representing and processing uncertainty in low level vision. Recently, probabilistic models have been proposed and used in vision. Sze liski''s method has a few distinguishing features that make this monograph im portant and attractive. First, he presents a systematic Bayesian probabilistic estimation framework in which we can define and compute the prior model, the sensor model, and the posterior model. Second, his method represents and computes explicitly not only the best estimates but also the level of uncertainty of those estimates using second order statistics, i.e., the variance and covariance. Third, the algorithms developed are computationally tractable for dense fields, such as depth maps constructed from stereo or range finder data, rather than just sparse data sets. Finally, Szeliski demonstrates successful applications of the method to several real world problems, including the generation of fractal surfaces, motion estimation without correspondence using sparse range data, and incremental depth from motion.

Computer Vision

Algorithms and Applications

AvRichard Szeliski

E-bok

PDF, Engelska, 2010

1 214 kr

Läs direkt efter köp

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.

More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques.

Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/.

Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Computer Vision

Algorithms and Applications

AvRichard Szeliski

Inbunden, Engelska, 2022

867 kr

Skickas inom 10-15 vardagar

Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projectsIncludes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decadeProvides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and softwareSuitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Computer Vision

Algorithms and Applications

AvRichard Szeliski

E-bok

PDF, Engelska, 2022

870 kr

Läs direkt efter köp

Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.

More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.

Topics and features:

Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projectsIncludes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decadeProvides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software

Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Large-Scale Visual Geo-Localization

AvAmir R. Zamir,Asaad Hakeemm. fl.

Inbunden, Engelska, 2016

1 297 kr

Skickas inom 10-15 vardagar

Thistimely and authoritative volume explores the bidirectional relationship betweenimages and locations. The text presents a comprehensive review of the state ofthe art in large-scale visual geo-localization, and discusses the emergingtrends in this area. Valuable insights are supplied by a pre-eminent selectionof experts in the field, into a varied range of real-world applications ofgeo-localization. Topics and features: discusses the latest methods to exploitinternet-scale image databases for devising geographically rich features andgeo-localizing query images at different scales; investigates geo-localizationtechniques that are built upon high-level and semantic cues; describes methodsthat perform precise localization by geometrically aligning the query imageagainst a 3D model; reviews techniques that accomplish image understandingassisted by the geo-location, as well as several approaches for geo-localizationunder practical, real-world settings.

Large-Scale Visual Geo-Localization

AvRichard Szeliski,Mubarak Shahm. fl.

E-bok

PDF, Engelska, 2016

1 179 kr

Läs direkt efter köp

Thistimely and authoritative volume explores the bidirectional relationship betweenimages and locations. The text presents a comprehensive review of the state ofthe art in large-scale visual geo-localization, and discusses the emergingtrends in this area. Valuable insights are supplied by a pre-eminent selectionof experts in the field, into a varied range of real-world applications ofgeo-localization. Topics and features: discusses the latest methods to exploitinternet-scale image databases for devising geographically rich features andgeo-localizing query images at different scales; investigates geo-localizationtechniques that are built upon high-level and semantic cues; describes methodsthat perform precise localization by geometrically aligning the query imageagainst a 3D model; reviews techniques that accomplish image understandingassisted by the geo-location, as well as several approaches for geo-localizationunder practical, real-world settings.

Large-Scale Visual Geo-Localization

AvAmir R. Zamir,Asaad Hakeemm. fl.

Häftad, Engelska, 2018

921 kr

Skickas inom 10-15 vardagar

Thistimely and authoritative volume explores the bidirectional relationship betweenimages and locations. The text presents a comprehensive review of the state ofthe art in large-scale visual geo-localization, and discusses the emergingtrends in this area. Valuable insights are supplied by a pre-eminent selectionof experts in the field, into a varied range of real-world applications ofgeo-localization. Topics and features: discusses the latest methods to exploitinternet-scale image databases for devising geographically rich features andgeo-localizing query images at different scales; investigates geo-localizationtechniques that are built upon high-level and semantic cues; describes methodsthat perform precise localization by geometrically aligning the query imageagainst a 3D model; reviews techniques that accomplish image understandingassisted by the geo-location, as well as several approaches for geo-localizationunder practical, real-world settings.

Vision Algorithms: Theory and Practice

International Workshop on Vision Algorithms Corfu, Greece, September 21-22, 1999 Proceedings

AvRichard Szeliski,Andrew Zissermanm. fl.

E-bok

PDF, Engelska, 2003

734 kr

Läs direkt efter köp

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Vision Algorithms held in Corfu, Greece in September 1999 in conjunction with ICCV''99.The 15 revised full papers presented were carefully reviewed and selected from 65 submissions; each paper is complemented by a brief transcription of the discussion that followed its presentation. Also included are two invited contributions and two expert reviews as well as a panel discussion. The volume spans the whole range of algorithms for geometric vision. The authors and volume editors succeeded in providing added value beyond a mere collection of papers and made the volume a state-of-the-art survey of their field.

Vision Algorithms: Theory and Practice

International Workshop on Vision Algorithms Corfu, Greece, September 21-22, 1999 Proceedings

AvA. Zisserman,Bill Triggsm. fl.

Häftad, Engelska, 2000

561 kr

Skickas inom 10-15 vardagar

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Vision Algorithms held in Corfu, Greece in September 1999 in conjunction with ICCV'99.The 15 revised full papers presented were carefully reviewed and selected from 65 submissions; each paper is complemented by a brief transcription of the discussion that followed its presentation. Also included are two invited contributions and two expert reviews as well as a panel discussion. The volume spans the whole range of algorithms for geometric vision. The authors and volume editors succeeded in providing added value beyond a mere collection of papers and made the volume a state-of-the-art survey of their field.

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Richard Szeliski – författare

Computer Vision

Bayesian Modeling of Uncertainty in Low-Level Vision

Bayesian Modeling of Uncertainty in Low-Level Vision

Bayesian Modeling of Uncertainty in Low-Level Vision

Computer Vision

Computer Vision

Computer Vision

Large-Scale Visual Geo-Localization

Large-Scale Visual Geo-Localization

Large-Scale Visual Geo-Localization

Vision Algorithms: Theory and Practice

Vision Algorithms: Theory and Practice

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