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ia/guidetocomputati0000baer.pdf
Guide to Computational Geometry Processing : Foundations, Algorithms, and Methods 🔍
J. Andreas Bærentzen; Jens Gravesen; François Anton; Henrik Aanæs Springer London Ltd, Springer Nature (Textbooks & Major Reference Works), London, 2012
英语 [en] · PDF · 18.6MB · 2012 · 📗 未知类型的图书 · 🚀/ia · Save
描述
This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features: presents an overview of the underlying mathematical theory, covering vector spaces, metric space, affine spaces, differential geometry, and finite difference methods for derivatives and differential equations; reviews geometry representations, including polygonal meshes, splines, and subdivision surfaces; examines techniques for computing curvature from polygonal meshes; describes algorithms for mesh smoothing, mesh parametrization, and mesh optimization and simplification; discusses point location databases and convex hulls of point sets; investigates the reconstruction of triangle meshes from point clouds, including methods for registration of point clouds and surface reconstruction; provides additional material at a supplementary website; includes self-study exercises throughout the text.
Erscheinungsdatum: 07.06.2012
备选作者
Bærentzen, J. Andreas, Gravesen, Jens, Anton, François, Aanæs, Henrik
备选作者
Jakob Andreas Bærentzen; Jens Gravesen; François Anton; Henrik Aanæs
备选作者
J. Andreas Bærentzen; Jens Gravesen; Francois Anton; Henrik Aanæs
备选作者
Baerentzen, Jakob Andreas
备选作者
Jakob Andreas B. Rentzen
备用出版商
New York: Springer
备用版本
United Kingdom and Ireland, United Kingdom
备用版本
London ; New York, ©2012
备用版本
2012, 2012-06-07
备用版本
2012, US, 2012
备用描述
-- Optical scanning is rapidly becoming ubiquitous. From industrial laser scanners to medical CT, MR and 3D ultrasound scanners, numerous organizations now have easy access to optical acquisition devices that provide huge volumes of image data. However, the raw geometry data acquired must first be processed before it is useful. -- This Guide to Computational Geometry Processing reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. This is balanced with an introduction to the theoretical and mathematical underpinnings of each technique, enabling the reader to not only implement a given method, but also to understand the ideas behind it, its limitations and its advantages. -- Topics and features: -- Presents an overview of the underlying mathematical theory, covering vector spaces, metric space, affine spaces, differential geometry, and finite difference methods for derivatives and differential equations -- Reviews geometry representations, including polygonal meshes, splines, and subdivision surfaces -- Examines techniques for computing curvature from polygonal meshes -- Describes algorithms for mesh smoothing, mesh parametrization, and mesh optimization and simplification -- Discusses point location databases and convex hulls of point sets -- Investigates the reconstruction of triangle meshes from point clouds, including methods for registration of point clouds and surface reconstruction -- Provides additional material at a supplementary website -- Includes self-study exercises throughout the text -- Graduate students will find this text a valuable, hands-on guide to developing key skills in geometry processing. The book will also serve as a useful reference for professionals wishing to improve their competency in this area
开源日期
2024-07-01
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