Editorial Review:
This well-accepted introduction to computational geometry is a textbook for high-level undergraduate and low-level graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In this third edition, besides revisions to the second edition, new sections discussing Voronoi diagrams of line segments, farthest-point Voronoi diagrams, and realistic input models have been added.
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Customer Reviews
Average Customer Rating: 
A very nice introduction to the field  2007-11-10
The authors did a great job of introducing the reader to all the important aspects of the field of computational geometry while keeping it simple and understandable.
Excellent Background 2007-06-13
This book is extremely well written, easy to understand, and actually is the standard text for Computational Geometry classes, as far as I know. The only thing I didn't like about it was that there seemed to be a few errors in some of the pseudocode. But, it's to be expected when publishing a textbook, and I think it'll probably be cleared up in future editions.
Overall, great book. I'd recommend it to anyone taking graphics or a computational geometry class.
good source of many methods  2006-02-24
The authors amass an impressive array of algorithms related to finding geometrical properties. Where these algorithms are performed on a computer. The book itself does not advocate any particular programming language. The algorithms are given in pseudocode, and you are expected to manually convert these to code in your choice of language. Given the calibre of the discussion in the text, which suggests that the readers are quite experienced, then this manual step should be easy to most.
There are numerous contexts in which the text might prove useful. Ranging from graphics to GIS to robotics. Thus, there is an entire chapter on the planning of robotic motion. The robot can in general translate and rotate.
Each chapter comes with an exercise set. Which helps make the book suitable as a graduate or even undergraduate text.
Important book but substandard layout and typesetting  2005-12-26
This is one of the really few computational geometry books available. It fills a niche and does it decently. However it could be better:
1. The chapter layout is not very good. There are many "revisiting this" and "we saw in chapter so-and-so".
2. The mathematical proofs are often written in a single paragraph full of "English" interspersed with mathematical notation, instead of the tried and true way of numbered equations and one-per explanations. This makes for disconcerting reading.
3. The book in general could have done with more math and code, and less "English", not to mention more and better diagrams -- they tend to be sparsely detailed (ie. a picture is worth only a hundred words). The arrangement of diagrams also needs to be better: some are in the margins, some are in the middle, again not easy and intuitive to follow.
Hopefully a future edition will address this issues.
Good Introduction but look elsewhere for detailed reference 2003-01-31
Pro:
(1) Each chapter begins with a practical example. For example, the chapter computing intersections of lines starts with a discussion of a map-making application that goes into enough detail to see how the algorithms they present would be useful. This is a considerable step up from the common practice in algorithms literature of motivation by way of vaguely mentioning some related field (i.e. "These string matching algorithms are useful in computational biology"). This book does a much better job of motivating the material it presents, but if you're primarily interested in the abstract problem, these sections can be skipped.(2) Each chapter is relatively self-contained. Feel free to skip ahead to subjects that interest you. (3) Surprisingly readable. Unlike most technical material, one can read an entire chapter in a single sitting without missing much. Generally, each chapter will develop a single algorithm for a single kind of problem. (4) It's very up to date. This second edition is less than two years old, it includes some new results in the field. Con:
(1) Algorithms are only given in pseudocode. The emphasis is on describing algorithms and data structures clearly and completely. If you're looking for a "cookbook" with code to copy and paste into an application, perhaps O'Rourke's "Computational Geometry in C" would be a better choice. (2) There are many important advanced results that are not discussed in the main text. An obvious example is the first chapter, which describes a well-known convex hull algorithm that takes O(n log n) time but algorithms that are faster for most inputs are mentioned only in the "Notes and Comments" at the end of the chapter. Someone interested in lots of gory details would be well-served to combine this book with Boissonnat and Yvinec's more detailed and mathematical "Algorithmic Geometry".
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