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Guide to Computational Geometry Processing -  Henrik Aanaes,  Francois Anton,  J. Andreas Baerentzen,  Jens Gravesen

Guide to Computational Geometry Processing (eBook)

Foundations, Algorithms, and Methods
eBook Download: PDF
2012 | 1. Auflage
XVIII, 352 Seiten
Springer London (Verlag)
978-1-4471-4075-7 (ISBN)
Systemvoraussetzungen
63,06 inkl. MwSt
(CHF 61,60)
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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.
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.

Part I: Mathematical Preliminaries
Vector Spaces, Affine Spaces, and Metric Spaces
Differential Geometry
Finite Difference Methods for Partial Differential Equations
Part II: Computational Geometry Processing
Polygonal Meshes
Splines
Subdivision
Curvature in Triangle Meshes
Mesh Smoothing and Variational Subdivision
Parametrization of Meshes
Simplifying and Optimizing Triangle Meshes
Spatial Data Indexing and Point Location
Convex Hulls
Triangle Mesh Generation: Delaunay Triangulation
3D Surface Registration via Iterative Closest Point (ICP)
Surface Reconstruction using Radial Basis Functions
Volumetric Methods for Surface Reconstruction and Manipulation
Isosurface Polygonization

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