
Curve and Surface Reconstruction
Algorithms with Mathematical Analysis
Tamal K. Dey(Author)
Cambridge University Press
Published on 16. October 2006
Book
Hardback
232 pages
978-0-521-86370-4 (ISBN)
Description
Many applications in science and engineering require a digital model of a real physical object. Advanced scanning technology has made it possible to scan such objects and generate point samples on their boundaries. This book, first published in 2007, shows how to compute a digital model from this point sample. After developing the basics of sampling theory and its connections to various geometric and topological properties, the author describes a suite of algorithms that have been designed for the reconstruction problem, including algorithms for surface reconstruction from dense samples, from samples that are not adequately dense and from noisy samples. Voronoi- and Delaunay-based techniques, implicit surface-based methods and Morse theory-based methods are covered. Scientists and engineers working in drug design, medical imaging, CAD, GIS, and many other areas will benefit from this first book on the subject.
Reviews / Votes
'The text is well written, and present the algorithms in a way that makes them quite understandable. Instead of presenting the algorithms as single, monolithic and complex methods, they are broken into parts that can be explained and mathematically analyzed in an order that makes clear how they are later composed into the larger task.' SIGACT NewsMore details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 18 mm
Weight
533 gr
ISBN-13
978-0-521-86370-4 (9780521863704)
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Schweitzer Classification
Other editions
Additional editions

Book
03/2011
Cambridge University Press
€59.10
Shipment within 15-20 days

E-Book
01/2007
1st Edition
Cambridge University Press
€41.49
Available for download
Person
Tamal K. Dey is Professor of Computer Science at the Ohio State University. He received his PhD from Purdue University. Before joining the Ohio State University he held faculty positions at Indian Institute of Technology, Kharagpur and research positions at the University of Illinois and Max Planck Institute. His primary research area is Computational Geometry and Computational Topology with applications to geometric modeling. He has authored more than fifty papers in this area and has lectured extensively on the topic of reconstruction and mesh generation in various academic forums.
Content
1. Basics; 2. Curve reconstruction; 3. Surface samples; 4. Surface reconstruction; 5. Undersampling; 6. Watertight reconstructions; 7. Noisy samples; 8. Noise and reconstruction; 9. Implicit surface based reconstructions; 10. Morse theoretic reconstructions.