Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing

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Guillaume Damiand Pascal Lienhardt

Combinatorial Maps

Efficient Data Structures for Computer Graphics and Image Processing

Guillaume Damiand, Pascal Lienhardt

$284

Hardback

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English

Apple Academic Press Inc.
19 September 2014

Database design & theory

A Versatile Framework for Handling Subdivided Geometric Objects

Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps.

Suitable for researchers and graduate students in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.

By: Guillaume Damiand, Pascal Lienhardt
Imprint: Apple Academic Press Inc.
Country of Publication: Canada
Dimensions: Height: 234mm, Width: 156mm, Spine: 25mm
Weight: 706g
ISBN: 9781482206524
ISBN 10: 1482206528
Pages: 406
Publication Date: 19 September 2014
Audience: College/higher education , Professional and scholarly , Further / Higher Education , Undergraduate
Format: Hardback
Publisher's Status: Active

Damiand, Guillaume; Lienhardt, Pascal

Reviews for Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing

An excellent technical teaching tool, especially recommended for college library mathematics and computer science shelves. -Midwest Book Review, January 2015 Guillaume Damiand and Pascal Lienhardt have produced an excellent book that discusses in full details a family of data structures for representing explicitly the connectivity of low-dimensional meshes, such as those used for some image and terrain processing or for modeling and animating geometric shapes. ... it provides a mathematically rigorous introduction to this area of research and gives the attentive reader a deep understanding of n-Gmaps and n-Maps, both as theoretical models and as practical data structures and associated operators. -Jarek Rossignac, Georgia Institute of Technology