Showing posts with label graphics. Show all posts
Showing posts with label graphics. Show all posts

Computer Vision: Algorithms and Applications (Texts in Computer Science) Review

Computer Vision: Algorithms and Applications (Texts in Computer Science)
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I have been reading the drafts of this book posted on Richard Szeliski's website, [...] , for about an year now. This book is written to cover almost all state-of-the-art research areas in computer vision and provides a solid introduction and reference. Unlike other books on vision, this book is about applications. The chapters are arranged keeping in mind the different key research areas which should be learned by a computer vision student. Apart from providing an overview, every chapter has abundant key references which direct the student for in-depth understanding of a particular area. This book is a welcome addition as literary resource for the computer vision community. Even though Szeliski has kept the digital version freely accessible in his site, this book as a hardbound version with color figures is definitely indispensable for every computer vision student and researcher. After Horn's landmark book, this book is here to stay as the premier computer vision book for years to come. I have started recommending this book for all the undergraduate and graduate students in my lab and I am planning to order a hardbound version for my personal bookshelf.
I strongly recommend this book for every computer vision enthusiast and I definitely feel that this book has the best content to interest people working in different areas of computer vision either in industry or academia. This book is surely the best book to learn computer vision at this point of time.

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The Visual Display of Quantitative Information Review

The Visual Display of Quantitative Information
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You know what's so good about this book? The research, that's what. In showing both good and bad graphic design, Tufte has examples from as far back as 1686, and many examples from the 18th,19th & 20th centuries and from many different countries.
Good graphic design, he argues, reveals the greatest number of ideas in the shortest time with the least ink in the smallest space. Interestingly, some of the best examples of this come from the pre-computer era, when graphics had to be drawn by hand (and therefore more thought had to go into their design, rather than the author just calling up the Bar Graph template on the desktop.) For example, that picture you can see on the front cover of the book is actually a train timetable that packs a whole list of arrivals and departures at many different stations into a single little picture. A better example (and the "best statistical graphic ever drawn") shows Napoleon's route through Europe. It shows a) the map b) where he went c) how many people were in his army at each point and d) the temperature on the way back that killed off his army. At a glance you can see the factors that led to his army losing. AND it was drawn by hand in 1885 and is little more than a line drawing!
He also gives examples of really bad design, (including "the worst graphic ever to make it to print"), and shows what makes it so bad. His examples prove that information-less, counter-intuitive graphics can still look dazzlingly pretty, even though they're useless. In some examples, he shows how small changes can make the difference between an awful graphic and a really good one. My favourite example of this is how he drew the inter-quartile ranges on the x and y axes of a scatterplot, thus adding more information to the graphic without cluttering it up.
In summary, there's a lot more to good graphic design than being an Adobe guru. Reading this book made me feel like a more discerning viewer of graphics!

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Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing Review

Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
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The book starts with a prologue of an under-determined linear system and how sparsity constraints help to solve it with the use of a Langrangian. Next the authors introduce the key idea of how certain norms promote sparsity. There are some good diagrams that really help the geometric intuition (though not as good as the ones by Donoho et al. in connection with Lasso). I really love the way they motivate and frame the entire field but still appeal to concept that most people who have studied linear algebra can relate to.
The first 6 chapters are a master piece in pedagogy. Except for the not so-standard usage of Spark as the measurement of coherence among elements of a dictionary. Mutual coherence is common and easier to grasp since it directly address the size of inner products. This leads to a rather jarring switch when RIP is introduced.
I am still puzzled why the authors do not appeal to frame theory. That leads to strange looking reference to self-dual frames and tight frames when the book never talked about frames.
I also wonder why the authors did not cite Boyd's great book. The treatment of log-barrier was sort of just another penalty function. The term log-barrier was never used in the book.
Overall I cannot put the book down and was especially grateful to the authors for introducing iterative shrinkage as a central theme to link many modern numerical algorithms to solve the basic sparse optimization problem.

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This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging.Sparse and Redundant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing.

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Production Rendering Review

Production Rendering
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If you are working in the field there is nowadays a lot of literature on how to write a renderer, and everybody has the silver-bullet to solve at last the rendering porblem.
This book thakes you through current technologies and gives you a very clear base on where to start when designing a modern renderer for high quality imagery.
It is as well really useful for all the people who want to do a really good job when using a renderer, making you understand what's going on, and what *should be going on* in your imagery

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Details the techniques used by experienced graphics software developers to implement feature film quality rendering engines.Brings together all the skills needed to develop a rendering system.

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Non-Photorealistic Computer Graphics: Modeling, Rendering, and Animation (The Morgan Kaufmann Series in Computer Graphics) Review

Non-Photorealistic Computer Graphics: Modeling, Rendering, and Animation (The Morgan Kaufmann Series in Computer Graphics)
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This book was an expensive mistake. There is almost nothing in it that can't be found in the Gooch & Gooch book at half the price. Other reviewers comment on the extensive pseudo code -- I found it thin and trivial. Just when a topic gets interesting the book moves on to another subject. It lacks depth.
Mr. & Mrs. Gooch have a far superior book.
This is the second Morgan Kaufmann book I've purchased. It seems they ONLY publish derivative works at inflated prices. (The first was a book on OpenGL which covered nothing that one couldn't find in th Red Book.) I shall by nothing more from them.

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Even as developments in photorealistic computer graphicscontinue to affect our work and leisure activities, practitioners and researchers are devoting more and more attention to non-photorealistic (NPR) techniques for generating images that appear to have been created by hand.These efforts benefit every field in which illustrations-thanks to their ability to clarify,emphasize, and convey very precise meanings-offer advantages over photographs. These fields include medicine, architecture, entertainment, education, geography, publishing, and visualization.Non-Photorealistic Computer Graphics is the first and only resource to examine non-photorealistic efforts in depth, providing detailed accounts of the major algorithms, as well as the background information and implementation advicereaders need to make headway with these increasingly important techniques.Already, an estimated 10% of computer graphics users require some form of non-photorealism. Strothotte and Schlechtweg's important new book is designed and destined to be the standard NPR reference for this large, diverse, and growing group of professionals.*Hard-to-find information needed by a wide range and growing number of computer graphics programmers and applications users.*Traces NPR principles and techniques back to their origins in human vision and perception.*Focuses on areas that stand to benefit most from advances in NPR, including medical and architectural illustration, cartography, and data visualization.*Presents algorithms for two and three-dimensional effects, using pseudo-code where needed to clarify complex steps.*Helps readers attain pen-and-ink, pencil-sketch, and painterly effects, in addition to other styles.*Explores specific challenges for NPR-including "wrong" marks, deformation, natural media, artistic technique, lighting, and dimensionality.*Includes a series of programming projects in which readers can apply the book's concepts and algorithms.

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Image-Based Modeling Review

Image-Based Modeling
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I am very happy to see this book by my colleague now in print. Many of the results have been already familiar to me. It summarizes years' efforts by Prof Long Quan and his students on 3d reconstruction and modeling, a fundamental topic in vision, graphics and visualization.
The book is comprehensive in that it is well structured into three parts:
the first fundamental vision geometry, the computational part, and the final application of vision methods to many of modeling and reconstruction topics.
In particular, I very much appreciated the first geometry part, as a more graphics and non-vision researcher myself, it's hard to read too many publications in the vision geometry area that has been well searched in the past two decades. With about 40 pages in a single chapter, chapter 3, we could have an overview of the vision geometry and quickly grasp the most essential algorithms exposed to a larger audience in a concise manner. The part 3 is mostly a collection of recent publications of the author and his students.
Given the potential of Google earth and Virtual Earth's efforts of turning everything into three-dimensional, the techniques systematically described in this book will likely guide its development in the future. I strongly recommend this book as an excellent text for graduate students and also a very useful resource for researchers in this field.

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Modeling and Simulation in Scilab/Scicos with ScicosLab 4.4 Review

Modeling and Simulation in Scilab/Scicos with ScicosLab 4.4
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The book "Modeling and Simulation with Scilab/Scicos"
is well written and understandable to
readers with the basic signal processing and programming
background.
The reader can refresh/improve the knowledge of
some basic control theory material, while at the
same time learns how to apply Scilab/Scicos at simulation and
modeling problems.
I worked with Matlab for many years before and I found
Scilab/Scicos a very powerful alternative to Matlab/Simulink
and is free!
I recommend strongly this book to any scientist/engineer that
plans to explore the benefits of the excellent open
source Scilab/Scicos environment.

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Scilab and its Scicos block diagram graphical editor, with a special emphasis on modeling and simulation tools. The first part is a detailed Scilab tutorial, and the second is dedicated to modeling and simulation of dynamical systems in Scicos. The concepts are illustrated through numerous examples, and all code used in the book is available to the reader.

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Digital Modeling of Material Appearance (The Morgan Kaufmann Series in Computer Graphics) Review

Digital Modeling of Material Appearance (The Morgan Kaufmann Series in Computer Graphics)
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This is the future of Computer Graphics. The book begins with a solid, foundational overview of light properties and their current forms of implementation. The book then gracefully develops the more advanced concepts and smoothly transitions into digital modeling of material appearance. In this subject of light there is no better compendium of knowledge, especially one that can educate due to its salient command of technical language that never obscures the concept underneath.

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Computer graphics systems are capable of generating stunningly realistic images of objects that have never physically existed. In order for computers to create these accurately detailed images, digital models of appearance must include robust data to give viewers a credible visual impression of the depicted materials. In particular, digital models demonstrating the nuances of how materials interact with light are essential to this capability. This is the first comprehensive work on the digital modeling of material appearance: it explains how models from physics and engineering are combined with keen observation skills for use in computer graphics rendering.Written by the foremost experts in appearance modeling and rendering, this book is for practitioners who want a general framework for understanding material modeling tools, and also for researchers pursuing the development of new modeling techniques. The text is not a "how to" guide for a particular software system. Instead, it provides a thorough discussion of foundations and detailed coverage of key advances.Practitioners and researchers in applications such as architecture, theater, product development, cultural heritage documentation, visual simulation and training, as well as traditional digital application areas such as feature film, television, and computer games, will benefit from this much needed resource.ABOUT THE AUTHORSJulie Dorsey and Holly Rushmeier are professors in the Computer Science Department at Yale University and co-directors of the Yale Computer Graphics Group. François Sillion is a senior researcher with INRIA (Institut National de Recherche en Informatique et Automatique), and director of its Grenoble Rhône-Alpes research center.* First comprehensive treatment of the digital modeling of material appearance;* Provides a foundation for modeling appearance, based on the physics of how light interacts with materials, how people perceive appearance, and the implications of rendering appearance on a digital computer;* An invaluable, one-stop resource for practitioners and researchers in a variety of fields dealing with the digital modeling of material appearance.

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Continuum Mechanics using Mathematica®: Fundamentals, Applications and Scientific Computing (Modeling and Simulation in Science, Engineering and Technology) Review

Continuum Mechanics using Mathematica®: Fundamentals, Applications and Scientific Computing (Modeling and Simulation in Science, Engineering and Technology)
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The mathematics discussed here is quite involved. Including tensor analysis, stress-strain relations and the non-linear Navier Stokes equation. Much of the work involves numerical analysis, as there are no analytic solutions to many problems.
You can treat the book as a standard, advanced text on the subject. But the added filip here is how it shows Mathematica can be used. Most general purpose texts on Mathematica involve simpler maths; high school or undergraduate level. Yet the program is quite powerful.
The book seems aimed at those scientists and engineers who are not primarily programmers. The idea is to let Mathematica offload much of the programming burden. The tradeoff might be that a loss of efficiency vis a vis custom code. But that might be acceptable to you.

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Modeling with Data: Tools and Techniques for Scientific Computing Review

Modeling with Data: Tools and Techniques for Scientific Computing
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Klemens teaches how to tame and understand a dataset the way it should be done: in C. Invest some time in this excellent book full of gentle humor and respect for the reader's intelligence. The payoffs will be immense. The best resource (a full set of programs used in the book) accompanying this book is available for FREE(!) on Klemens's website!

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Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results.

Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date.

Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.


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Texturing and Modeling, Third Edition: A Procedural Approach (The Morgan Kaufmann Series in Computer Graphics) Review

Texturing and Modeling, Third Edition: A Procedural Approach (The Morgan Kaufmann Series in Computer Graphics)
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This is an update of a classic book on procedural texturing and modeling by the main founders of the field. The book presents lengthy discussions of classical procedural texturing using various noise functions of the sort originated by Ken Perlin (one of the authors). It discusses newer texturing techniques such as cellular texturing, which can be used, for example, to create convincing stone patterns. Other chapters focus on animating solid textures (e.g. marble forming, volumetric gasses, etc.), fractal terrain generation, and tips for utilizing existing graphics APIs and hardware for realtime procedural texturing. This is only a sampling of the topics covered.
Code samples in C and RenderMan are given throughout, although most algorithms are given in only one of those languages. This can be a bit of a problem, as many readers will probably not have access to a RenderMan implementation. Nevertheless, it is not too difficult to translate the RenderMan code into C code in many instances.
The biggest drawback to this book is its lack of rigorous technical coverage. The decision to omit many mathematical details was a conscious choice on the part of the authors. Instead the book is mostly prose discussion of the techniques and the coarse descriptions of the underlying concepts. Although the prose is mostly clear, many times I felt myself in need of more specific, technical details. Fortunately, the book's authors are the primary researchers in this field and most of the ideas in the book have been published in academic journals. It was very easy to supplement the book with these primary sources.
Overall I found this to be a very interesting and useful book, with many algorithms essentially ready-to-run right out of the book. It would get five stars, except for the lack of technical and mathematical details mentioned above. Every serious worker in graphics needs to have this book on their shelf. I use mine often.

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The third edition of this classic tutorial and reference on procedural texturing and modeling is thoroughly updated to meet the needs of today's 3D graphics professionals and students. New for this edition are chapters devoted to real-time issues, cellular texturing, geometric instancing, hardware acceleration, futuristic environments, and virtual universes. In addition, the familiar authoritative chapters on which readers have come to rely contain all-new material covering L-systems, particle systems, scene graphs, spot geometry, bump mapping, cloud modeling, and noise improvements. There are many new spectacular color images to enjoy, especially in this edition's full-color format.As in the previous editions, the authors, who are the creators of the methods they discuss, provide extensive, practical explanations of widely accepted techniques as well as insights into designing new ones. New to the third edition are chapters by two well-known contributors: Bill Mark of NVIDIA and John Hart of the University of Illinois at Urbana-Champaign on state-of-the-art topics not covered in former editions.An accompanying Web site (www.texturingandmodeling.com) contains all of the book's sample code in C code segments (all updated to the ANSI C Standard) or in RenderMan shading language, plus files of many magnificent full-color illustrations.No other book on the market contains the breadth of theoretical and practical information necessary for applying procedural methods. More than ever, Texturing & Modeling remains the chosen resource for professionals and advanced students in computer graphics and animation.*New chapters on: procedural real-time shading by Bill Mark, procedural geometric instancing and real-time solid texturing by John Hart, hardware acceleration strategies by David Ebert, cellular texturing by Steven Worley, and procedural planets and virtual universes by Ken Musgrave.*New material on Perlin Noise by Ken Perlin.*Printed in full color throughout.*Companion Web site contains revised sample code and dozens of images.

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