This is a how-to book for solving geometric problems robustly or error free in actual practice. The contents and accompanying source code are based on the feature requests and feedback received from industry professionals and academics who want both the descriptions and source code for implementations of geometric algorithms. The book provides a framework for geometric computing using several arithmetic systems and describes how to select the appropriate system for the problem at hand.
Key Features:
A framework of arithmetic systems that can be applied to many geometric algorithms to obtain robust or error-free implementations
Detailed derivations for algorithms that lead to implementable code
Teaching the readers how to use the book concepts in deriving algorithms in their fields of application
The Geometric Tools Library, a repository of well-tested code at the Geometric Tools website, https://www.geometrictools.com, that implements the book concepts
This is a how-to book for solving geometric problems robustly or error free in actual practice. The contents and accompanying source code are based on the feature requests and feedback received from industry professionals and academics who want both the descriptions and source code for implementations of geometric algorithms. The book provides a framework for geometric computing using several arithmetic systems and describes how to select the appropriate system for the problem at hand.
Key Features:
A framework of arithmetic systems that can be applied to many geometric algorithms to obtain robust or error-free implementations
Detailed derivations for algorithms that lead to implementable code
Teaching the readers how to use the book concepts in deriving algorithms in their fields of application
The Geometric Tools Library, a repository of well-tested code at the Geometric Tools website, https://www.geometrictools.com, that implements the book concepts
A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R CodeThe A-Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical...
From the foreword by Thomas Huang: "During the past decade, researchers in computer vision have found that probabilistic machine learning methods are extremely powerful. This ...
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