000			04281nam a22003975i 4500
001			287403
003			MX-SnUAN
005			20160429154546.0
007			cr nn 008mamaa
008			150903s2012 xxk| o |||| 0|eng d
020			_a9781447140757 _99781447140757
024	7		_a10.1007/9781447140757 _2doi
035			_avtls000339711
039		9	_a201509030318 _bVLOAD _c201404300404 _dVLOAD _y201402060942 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA76.9.M35
100	1		_aBærentzen, Jakob Andreas. _eautor _9316562
245	1	0	_aGuide to Computational Geometry Processing : _bFoundations, Algorithms, and Methods / _cby Jakob Andreas Bærentzen, Jens Gravesen, François Anton, Henrik Aanæs.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2012.
300			_axviii, 325 páginas 174 ilustraciones, 17 ilustraciones en color. _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aPart 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.
520			_aOptical 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.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aGravesen, Jens. _eautor _9316563
700	1		_aAnton, François. _eautor _9316564
700	1		_aAanæs, Henrik. _eautor _9316565
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781447140740
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4471-4075-7 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c287403 _d287403