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Computational Geometry
The following report compares books using the SERCount Rating (base on the result count from the search engine).
Rating: 4.36/5 from 11 reviews Interesting read, excellent theory, no codeThe best computational geometry book!I also completely disagree with the one-star review below. The "Dutch book" is the clearest, most complete, most up-to-date, best designed, best illustrated computational geometry textbook out there. Some of the material may be a bit advanced for undergraduates (and for those people I would recommend Joe O'Rourke's excellent "Computational Geometry in C"), but for graduate students and other researchers who want to learn computational geometry, this book is absolutely essential. This is an algorithms textbook, though, not a textbook full of code. You will not find compilable code in the author's favorite programming language du jour -- this may be what the first reviewer meant by "desperately needed details". What you will find is clear, correct, well-motivated explanations of the underlying algorithms, data structures, and mathematics. The book does have a few faults. The motivating examples are often forced ("mixing things" for convex hulls??). The authors deliberately chose to show only one algorithm for each problem they consider, and occasionally the algorithm they chose is not the simplest or most efficient. But these are minor points. If you're going to buy just one computational geometry book, this is the one to get. Good Introduction but look elsewhere for detailed referencePro: (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: (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". | ||||||||||||||||||||
Although I have yet to actually implement one of the algorithms in the book directly, I was exposed to a number of general techniques which I have used, such as randomized techniques to eliminate pathological worst-case performance problems, and various space partitioning techniques.
The algorithms are all presented in pseudocode, unfortunately, which is the reason for only 4 out of 5 stars. Also, some important details are omitted which make a few of their algorithms practically useless (although they are interesting theoritically). For example, there is an algorithm for pathfinding and collision avoidance for a translating (but not ROTATING!) robot.
If you're lookin for a computational geometry bible, this isn't it. But there are certainly some gems in this book and it is a very interesting read.