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Curve and Surface Reconstruction

Curve and Surface Reconstruction

Curve and Surface Reconstruction

Algorithms with Mathematical Analysis
Tamal K. Dey, Ohio State University
March 2011
Paperback
9780521175180

    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.

    • Provides fundamentals of point cloud data processing
    • Algorithms with correctness proofs are presented
    • Many figures, a set of exercises, and a brief history for each chapter

    Reviews & endorsements

    "The text is well written, and presents the algorithms in a way that makes them quite understandable."
    Matthew J. Sottile, SIGACT News

    See more reviews

    Product details

    March 2011
    Paperback
    9780521175180
    230 pages
    229 × 152 × 13 mm
    0.34kg
    Available

    Table of Contents

    • 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.