Overview
- Reviews algebraic techniques for geometrical problems in computer science and engineering, and the relationships between them
- Provides hands-on review exercises throughout the book, together with helpful chapter summaries
- Includes contributions from an international community of experts, spanning a broad range of disciplines
- Includes supplementary material: sn.pub/extras
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About this book
This highly practical Guide to Geometric Algebra in Practice reviews algebraic techniques for geometrical problems in computer science and engineering, and the relationships between them. The topics covered range from powerful new theoretical developments, to successful applications, and the development of new software and hardware tools. Topics and features: provides hands-on review exercises throughout the book, together with helpful chapter summaries; presents a concise introductory tutorial to conformal geometric algebra (CGA) in the appendices; examines the application of CGA for the description of rigid body motion, interpolation and tracking, and image processing; reviews the employment of GA in theorem proving and combinatorics; discusses the geometric algebra of lines, lower-dimensional algebras, and other alternatives to 5-dimensional CGA; proposes applications of coordinate-free methods of GA for differential geometry.
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Table of contents (21 chapters)
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Front Matter
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Rigid Body Motion
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Front Matter
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Image Processing
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Front Matter
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Theorem Proving and Combinatorics
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Front Matter
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Editors and Affiliations
Bibliographic Information
Book Title: Guide to Geometric Algebra in Practice
Editors: Leo Dorst, Joan Lasenby
DOI: https://doi.org/10.1007/978-0-85729-811-9
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London Limited 2011
Hardcover ISBN: 978-0-85729-810-2Published: 29 August 2011
Softcover ISBN: 978-1-4471-5897-4Published: 06 September 2014
eBook ISBN: 978-0-85729-811-9Published: 28 August 2011
Edition Number: 1
Number of Pages: XVII, 458
Topics: Math Applications in Computer Science, Symbolic and Algebraic Manipulation, Computer Graphics, Artificial Intelligence, Image Processing and Computer Vision, Computer-Aided Engineering (CAD, CAE) and Design