Reviews (7)

A must for every renderman user but dated.
For a long time this was the one and only reference book available to users and without it I would still be trying to decipher the Renderman documentation from Pixar.

Much of the content in the book describes the C programming API used to write programs to create computer graphics and animation.It's been my experience in this day and age, that most users skip over all the C stuff and dive right into the Shading Language.After all, we have animation programs to take care of setting up a scene and moving objects around, we just want to make them look pretty.

Reading through the entire book will undoubtedly give you a better understanding of how renderman and computer graphics works.And is definitely a must for anyone that wants to program applications to work with renderman, but for most people wanting to use renderman to color and light it's all a bit much to take in.We must remind ourselves and look at the cover to see who the book was written for 'A "Programmer's" Guide to Realistic Computer Graphics'.

Overall an excellent and informative companion that I refer to almost every time I write a shader.If it were brought up to date (and included the RIB specification) it would be deserving of another star or two.

If you are trying to choose between this book and "Advanced Renderman" don't bother... get both of them."The RenderMan Companion" is more of a reference book where "Advanced RenderMan" explores advaced topics with some tutorial components and limited reference, picking up where the Companion left off.Even the authors of "Advanced Renderman" recommend that you keep this book handy.

A good technical introduction to RenderMan
For me, a beginner, the book was a little heavy and terse. Although it is written well, some concepts require more explaination. Also, the use of the C binded RenderMan API, is a little old, and makes it annoying when writing a RIB from the examples in the book. Regardless of the level of expertise required beforehand, it is a great reference book, and provides a good reference to all RenderMan users.

Editorial Review

More powerful and inspiring than the superheroes it moves on the big screen, the RenderMan 3-D graphics engine pushes animation toward the photorealistic as anyone who has seen A Bug's Life, The Iron Giant, or the Toy Story can attest.Advanced RenderMan, written by two long-time employees of Pixar Animation and early participants who helped define the RenderMan standard, is a clear, concise, and technical exploration of this computer graphics and animation rendering tool.

The first section introduces RenderMan, computer graphics concepts, and mathematics, followed by a section on "Scene Description." This includes chapters on "Describing Models and Scenes in RenderMan" and "Handling Complexity in Photorealistic Scenes."

Sections 3 and 4, "Shading," and "Tricks of the Trade" supply the meat of the book and make it worth the cost of admission. These sections include examples and insight from not only a technical perspective but also a cinematic one. The chapter "Storytelling Through Lighting" should be required reading for beginning computer animation artists.

There are numerous color plates, including some rendering tests from Toy Story. These show the same scene (Andy's room) using different lighting and color palettes, each suggesting a different time of day.

Given the difficulty of the book's subject, 3-D artists or animators with limited technical chops, amateurs, or hobbyists might be better served by something more general. This is, however, an outstanding reference for CG technical directors or anyone with experience in graphics and 3-D programming. It is filled with coding examples used to create RenderMan shaders and case studies citing which techniques were used to create a specific look in, for example, Toy Story or A Bug's Life.

Editorial Review

One would think that the title of Tomas Moller's and Eric Haines's book, Real-Time Rendering, would be a contradiction in terms. How can such a computationally intensive process as rendering computer graphics ever hope to be done on the fly, in the blink of an eye, without delay--in short, in real time?

The term rendering, as it applies to computer graphics, refers to the mathematically intensive process of creating a picture or sequence of frames based on geometry. The duration of this process is dependent on the complexity of the scene (a forest with many trees and thousands of leaves will take much longer to render than a scene consisting of a white box over a gray background) and the speed of the hardware doing the calculations.

When Pixar's Toy Story was first released, the computer animation community was all abuzz with how it was done, and someone at Pixar mentioned that over 100 SGI workstations were used for rendering the frames over the course of almost two years. Someone else extrapolated this data and figured out that the same movie could have been rendered on one contemporary PC over the course of about 80 years.

The authors deftly answer the question, not only asserting that it can be done, but since this book is a programmer's guide, they list snippets of programming algorithms that help outline how it can be done.

Because the software and hardware is constantly and rapidly evolving due to the insatiable need for more realistic and complex graphics, the book avoids getting too specific. To quote the authors, "The field is rapidly evolving, and so it is a moving target." This lack of specificity doesn't detract from the usefulness of the book, though. Instead, it works at a higher, more abstract level, describing approaches to rendering techniques using generic algorithms. It is up to the programmer to apply these methods to the specific program or system on which it is to be implemented.

Reviews (1)

Isbn: 0201126494
Sales Rank: 1759947
Subjects:  1. Algebra - Linear    2. Algebras, Linear    3. Linear Algebra    4. Mathematical optimization    5. Mathematics    6. Numerical calculations    7. Science/Mathematics   

Reviews (5)

Nice balance of theory with code
This book was pleasantly surprising:I had expected to see code presented with minimal motivation or discussion of the underlying ideas -- something of a "Computational Geometry for Dummies" sort of book.That's not the case at all.This is a bona fide textbook on the subject, suitable for an undergraduate course.
It covers all of the the "classical" topics: convex hulls, line segment intersection, polygon triangulation, Voronoi diagrams, motion planning.

The mode of presentation -- supporting a discussion of the theories with implementable code -- is actually a bit refreshing.For comparison:Other books, when discussing the line segment intersection problem (ie: Given a set of line segments, find all of their intersection points) simply assume that computing the intersection of a pair of segments can be done in constant time.This is not an especially difficult problem, but the discussion seems more complete with a brief description of how this might be done.The same can be said about other primitive tests and operations in other algorithms.

Overall, this book can stand alone as an excellent introduction to computational geometry, but a serious student in the subject will want more: perhaps Preparata and Shamos or de Berg et. al.

Very hepful
Anyone who is involved in areas such as computer graphics, computational radiology, robot vision, or visualization software should have a copy of this book. The author has done a fine job of introducing the most important algorithms in computational geometry, choosing the C language for their implementation. The choice of C might be somewhat dated now, since C++ is now beginning to dominate computational geometry, but readers who are actually programming these algorithms using C++ can easily extend the ones in the book to C++. Not all of the algorithms in the book are implemented into C, unfortunately, but the clarity of presentation is done well enough to make this implementation a fairly straightforward task. My interest in the book came from a need to design and implement algorithms for polyhedra in VRML and toric varieties in algebraic geometry. This book, along with others, was a great help in that regard. The running time of these algorithms was not really an issue with me, so the detail the author spends on discussing the complexity of the algorithms was not a concern. Readers who need to pay attention to running-time issues will appreciate his discussion of them for the algorithms that are presented.

The ability to visualize objects in an abstract subject like algebraic geometry boils down to, in the case of toric varieties, to a consideration of how to manipulate polytopes geometrically. A major portion of the book, if not all of it, is devoted to the computational geometry of polyhedra. Because it is an introductory book, some more advanced topics, such as Bayesian methods to find similarities between polyhedra, and neural network approaches to classifying polyhedral objects are not treated. Readers who need to do such things will be well-prepared for them after a study of this book. In addition, there are good exercises assigned at the end of each chapter, so the book could be used in the classroom. Some readers will however choose to use it as a reference source, and it would be a good one, for the author gives references to topics that he only touched upon in the book.

Some particular areas that were treated especially well were: 1. The discussion on data structures for surfaces of polyhedra. Although not very general, since he choose to deal with only triangulated polytopes, readers who need to be more general will have a good start in this discussion. 2. The discussion on volume overflow and how to deal with it using robust computation. 3. The discussion, albeit short, of the randomized incremental algorithm. 4. The treatment on the minimum spanning tree and Kruskal's algorithm. Communication network performance optimization is now a major application of this algorithm and others in graph theory, including the author's later discussion of Dijkstra's algorithm.

Reviews (1)

Editorial Review

Although computer graphics applications have grown remarkably easy to use, there is absolutely nothing simple about how they work. One of the most difficult aspects is the creation of smooth or organic shapes using the inherently flat polygon approach to modeling. Subdivision Methods for Geometric Design describes the contemporary approach to solving this problem.

It is not an unheard-of practice--large computer animation studios such as Pixar not only use this approach, but some of their researchers helped pioneer it. Learning how subdivisions work, though, and applying them in your application is the tricky part. In this valuable textbook, the authors attempt to explain the approach and usage of this valuable technique.

Spanning eight chapters and 275 pages of text, this hardcover is divided loosely into three parts. The first part is an introduction to subdivision and techniques for creating subdivision schemes. The second part, chapters 4 through 6, focuses on "a new differential method for constructing subdivision schemes." Later sections explore the techniques and practice of applying subdivision to polyhedral meshes, most commonly found in computer modeling systems where smooth forms are desirable.

Editorial Review

Reviews (6)

excellent
This book is ABSOLUTELY among the best in the area of computational mathematics.It covers from the basics to the trendy applications, which is the biggest satisfaction I got from spending money on it.It is more than a collection of papers (no kidding!), since the contents have a good interior coherence if you read it carefully rather than browsing it like a novel.And for the those fancy pictures in the book, all I can say is that 'a picture is worth than thousands of words' - it is especially true in the area of graphics.You guys who care about SIGGRAPH should know better.More than that, this book does give you the numerical recipe for you to DIY these simulations on your own computer, besides the mathematics behind all those sexy results.Anyway, this book is worth every penny you spent!

Disappointing
The book is merely a collection of (way too shortened) papers from the same authors and others. Most of the time there is no coherent link between the different parts. Worst, there are many examples but very little details for each of them, when I start reading a chapter, I always end up getting the related papers from the internet which are in most cases clearer and more complete, and also there are free.

I really respect the achievement made in cg, image processing, and computational physics made by the authors (so I will give it 2 stars), but once you are done looking at the fancy pictures, you won't get much from this book apart from its bibliographic references.

I would rather recommend the book "Level set methods and fast marching methods" from J.A. Sethian, the mathematical aspects are better covered and it manages to take things into perspective while still remaining very practical.

Reviews (2)

Teaches good mathematical programming techniques
The book does a very good job in teaching non-discrete mathematical programming techniques. But, it is not an introductory book. The reader is supposed to know linear algebra and numerical analysis to a certain extent. Most of the modern techniques are presented, but the layout is a little chaotic- the sequence of subjects could be made better. So, I would have preferred to give it 4.5 stars (which is impossible). However, that does not take away the fact that the book is excellent. I have used it primarily for modelling financial portfolios, and I am sure it can be used as a guide for other applications.

Conclusion: A little difficult, but well worth the time and money involved

Nice but could be better!
This book by Nocedal and Wright has several attractive features.For one, it is probably the most "state-of-the-art" of the existing texts in optimization and as such covers most of the modern methods.It also hasa nice section on LP (simplex as well as interior point methods) forsomeone interested in a course on optimization as opposed to NONLINEARoptimization (which is what I was looking for).Another strength is thatit covers many of the algebra-related details very well. My only majorcomplaint is that it seems to not get into any of the methods designedspecifically for convex programs - these while admittedly less general areoften very powerful.For example, there is NO mention even of GeometricProgramming which has wide application in design.The convex simplexmethod also isn't mentioned anywhere.Finally,I wonder why there is nomention of the generalized reduced gradient (GRG) method.

Reviews (4)

PhD Student
This book is really just an introduction to NLA and intended for the novice although it assumes some LA background.It is not necessary to read this if you plan PhD studies in the field since the book is only an introduction to the material and is honestly too simple.Read anything by Bjorck or Van Loan if you are a serious PhD student and want to do research in the field of NLA.This book is written for students that really don't plan research in the field of NLA but rather may need some skill level in NLA to perform their job or their own own research which may have some NLA exposure.

This book grows on you
I used this text for a two-semester graduate sequence in numerical linear algebra (NLA) while I was a graduate student in the Mathematics Department at The University of Kentucky.If you do not have a substantial background in linear algebra and numerical analysis, which I did not when I first used this book, the material covered and the presentation can seem to be quite daunting.But while the presentation is very thorough, it is not unnecessarily so.After I had used this text for about three months, I grew accustomed to the very detailed nature of the writing and grateful for the sheer level of information contained in a meer 419 pages.

Many introductury numerical analysis books include several chapters covering the commonly used algorithms in NLA but usually not in complete detail.While this format is friendlier to use for an overview of the "basics," in the real world, the standard ways of solving numerical systems such as GEPP, SVD, QR, Cholesky decompostions, Gauss-Siedel iterations, and other methods do not always work in a nice cookbook-like fashion.When one of these standard methods that engineers and research scientists use to solve "standard" problems fails, and it will sometimes, this book will give you a good starting point to figure out what went wrong and what alternate methods can be used to solve a linear system that is not as easy as it first appeared to be.

If you are learning NLA, you are probably doing so because you either want to or have to apply it in your professional life, by which I mean your job or the job that you hope to get.In my current position, I develop and design statistical and deterministic simulators for human genetics research.And when I need to used Cholesky decompostions, SVD's, and other NLA methods, I always consult this book to review how these methods work and, more importantly, what innocent looking data will cause these methods to fail silently - in other words, give results that look reasonable, but are completely wrong.In conclusion, this book is not the easiest to read.But it is one of the best resources available when you need to learn how to handle basic and not-so-basic problems in the field of NLA.