Guide to Computational Geometry Processing

Guide to Computational Geometry Processing

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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.12. Spatial. Data. Indexing. and. Point. Location. This chapter is devoted to the spatial data structures that can be used in order to optimize the access to spatial objects, needed in many of the other chapters of this part, and in particular, ... Section 12.1 will present the context of spatial data indexing: databases, spatial data handling and spatial data ... 12.1 Databases, Spatial Data Handling and Spatial Data Models For a more in-depth coverage of databases, the reader can refer to [1].

Title:Guide to Computational Geometry Processing
Author: J. Andreas Bærentzen, Jens Gravesen, Francois Anton, Henrik Aanæs
Publisher:Springer Science & Business Media - 2012-05-31

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