在线阅读本书
Within the last decade, Geometric Algebra (GA) has emerged as a powerful alternative to classical matrix algebra as a comprehensive conceptual language and computational system for computer science. This book will serve as a standard introduction and reference to the subject for students and experts alike. As a textbook, it provides a thorough grounding in the fundamentals of GA, with many illustrations, exercises and applications. Experts will delight in the refreshing perspective GA gives to every topic, large and small. -David Hestenes, Distinguished research Professor, Department of Physics, Arizona State University Geometric Algebra is becoming increasingly important in computer science. This book is a comprehensive introduction to Geometric Algebra with detailed descriptions of important applications. While requiring serious study, it has deep and powerful insights into GA's usage. It has excellent discussions of how to actually implement GA on the computer. -Dr. Alyn Rockwood, CTO, FreeDesign, Inc. Longmont, Colorado Until recently, almost all of the interactions between objects in virtual 3D worlds have been based on calculations performed using linear algebra. Linear algebra relies heavily on coordinates, however, which can make many geometric programming tasks very specific and complex-often a lot of effort is required to bring about even modest performance enhancements. Although linear algebra is an efficient way to specify low-level computations, it is not a suitable high-level language for geometric programming. Geometric Algebra for Computer Science presents a compelling alternative to the limitations of linear algebra. Geometric algebra, or GA, is a compact, time-effective, and performance-enhancing way to represent the geometry of 3D objects in computer programs. In this book you will find an introduction to GA that will give you a strong grasp of its relationship to linear algebra and its significance for your work. You will learn how to use GA to represent objects and perform geometric operations on them. And you will begin mastering proven techniques for making GA an integral part of your applications in a way that simplifies your code without slowing it down. Features Explains GA as a natural extension of linear algebra and conveys its significance for 3D programming of geometry in graphics, vision, and robotics. Systematically explores the concepts and techniques that are key to representing elementary objects and geometric operators using GA. Covers in detail the conformal model, a convenient way to implement 3D geometry using a 5D representation space. Presents effective approaches to making GA an integral part of your programming. Includes numerous drills and programming exercises helpful for both students and practitioners. Companion web site includes links to GAViewer, a program that will allow you to interact with many of the 3D figures in the book, and Gaigen 2, the platform for the instructive programming exercises that conclude each chapter. About the Authors Leo Dorst is Assistant Professor of Computer Science at the University of Amsterdam, where his research focuses on geometrical issues in robotics and computer vision. He earned M.Sc. and Ph.D. degrees from Delft University of Technology and received a NYIPLA Inventor of the Year award in 2005 for his work in robot path planning. Daniel Fontijne holds a Master's degree in artificial Intelligence and is a Ph.D. candidate in Computer Science at the University of Amsterdam. His main professional interests are computer graphics, motion capture, and computer vision. Stephen Mann is Associate Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, where his research focuses on geometric modeling and computer graphics. He has a B.A. in Computer Science and Pure Mathematics from the University of California, Berkeley, and a Ph.D. in Computer Science and Engineering from the University of Washington.
* The first book on Geometric Algebra for programmers in computer graphics and entertainment computing * Written by leaders in the field providing essential information on this new technique for 3D graphics * This full colour book includes a website with GAViewer, a program to experiment with GA
评分
评分
评分
评分
说实话,刚翻开这本书的时候,我被它的数学深度小小的震撼了一下,这绝对不是一本面向初学者的“入门速成”读物。它的叙事节奏非常慢,可以说是步步为营,每一章都像是为前一章的结论铺设无可辩驳的逻辑地基。我尤其欣赏它在引入新的代数结构时,总是先回顾经典向量代数和复数的局限性,然后自然而然地引出几何代数如何以更统一、更简洁的方式统一这些工具。这种“问题驱动”的教学法非常能抓住读者的注意力,让人忍不住想知道:“那么,几何代数如何解决我们现在遇到的这个瓶颈?”书中对物理建模和三维几何处理的章节,简直是教科书级别的典范。它展示了如何用单个的多矢量表达式来描述点积、叉积乃至更高维度的投影和反射,这极大地简化了我的三维重建项目中的代码逻辑。虽然某些证明过程略显冗长,需要读者投入大量的精力去细细品味,但一旦理解了背后的几何意义,那种豁然开朗的感觉是任何速成班都无法给予的。这本书更像是一位耐心的导师,它不急于让你学会“应用”,而是先让你学会“思考”几何问题的正确方式。
评分作为一名有着多年软件开发经验的工程师,我最看重的是工具的实用性和优雅性。这本书虽然数学根基深厚,但绝非纸上谈兵的纯理论著作。它在论述完核心概念后,会紧接着探讨这些概念在现代计算中的体现。例如,它如何将高效的碰撞检测、光线追踪中的击中测试,以及SLAM(同步定位与地图构建)中的姿态估计,通过几何代数的视角进行重新审视。这种连接点非常关键,它让读者不再觉得学习这门技术只是为了完成一个抽象的数学作业,而是为了掌握一种能写出更简洁、更鲁棒、且不易出错的代码的“超能力”。我特别留意了关于“度量”(metric)和“共变性”(covariance)的讨论,这对于处理非欧几里得空间(比如流形学习或非线性优化)至关重要,而这本书将其与基础代数结构紧密结合。阅读过程中,我不断地将书中的概念映射到我过去处理过的项目中,发现许多过去的复杂实现,如果使用几何代数,将会大大简化。这本书就像是一份高级工具箱的说明书,教会你如何用最少、最精良的工具去完成最复杂的工作。
评分这本书的行文风格属于“学术精品”那一类,它并不试图迎合快速阅读的潮流,而是要求读者保持专注和耐心。它的成功之处在于,它为那些在传统多元微积分和线性代数学习中感到困惑的读者提供了一个全新的视角——一个真正能“看到”高维空间的视角。我个人认为,对于那些深入到几何深度学习、或者研究新型渲染管线的读者而言,这本书几乎是必不可少的参考书。它不是简单地介绍一个新的数学工具箱,而是提供了一种全新的思维范式。书中对逆运算、微分算子在几何代数框架下的表达方式的讨论,清晰地展示了它在处理微积分问题上的巨大潜力,这在传统向量演算中往往需要大量的坐标变换和复杂的链式法则。作者对细节的关注令人印象深刻,例如,对不同代数基底选择对计算效率影响的探讨,这对于优化实际算法至关重要。总而言之,这是一部值得反复研读的著作,每一次重读都会从中发现新的层次和更深的洞见,它彻底改变了我对几何计算的理解方式。
评分这本书的封面设计充满了未来感,那种深邃的蓝色背景上交织着复杂的几何图形,让人立刻联想到高等数学和前沿技术。我是在寻找一种能将抽象的线性代数概念与计算机图形学、机器学习中的实际应用桥接起来的教材时发现它的。拿到手后,第一印象是它的分量和厚度,这通常意味着内容的深度和广度。作者的写作风格非常严谨,开篇就奠定了扎实的数学基础,没有丝毫敷衍。对于一个希望从根本上理解几何运算如何影响算法效率的人来说,这种自底向上的构建方式是极其宝贵的。书中对 Clifford 代数的介绍尤为精彩,它不像传统教科书那样只是罗列公式,而是用清晰的几何直觉来引导读者理解向量、标量、双矢量(bivectors)和多矢量(multivectors)之间的内在联系。特别是关于旋转和变换的讨论,用代数的方法优雅地解决了过去需要繁琐矩阵运算才能完成的任务,这在资源受限的嵌入式系统或需要高性能计算的领域具有巨大的实际价值。整体而言,这本书的排版清晰,图示精美,即使是初次接触这个领域的读者,也能感受到作者试图将“难懂”的数学概念“可视化”的良苦用心。它无疑是进入这一交叉领域的一把坚实钥匙。
评分这本书的价值,很大程度上在于它对“统一性”的追求。在计算机科学的许多分支——从计算机图形学(CG)到传感器融合,再到机器人学——我们常常需要处理不同类型的几何对象(点、线、面、体)以及它们之间的关系。传统方法往往需要为每种情况建立一套独立的数学工具,比如欧拉角、四元数、旋转矩阵等,这些工具之间转换起来麻烦且容易引入奇异性问题(比如万向节死锁)。这本书巧妙地展示了如何用单一的代数框架来驾驭所有这些操作。通过构建合适的代数空间,旋转、缩放、平移,乃至更复杂的形变,都可以被表述为多矢量在特定代数群下的乘法。这对于开发通用型的几何处理库具有里程碑式的意义。我发现,书中关于投影和反射的章节尤其具有启发性,它揭示了为什么某些几何算法在直觉上是“优美”的,而不仅仅是“有效”的。此外,书中的习题设计也非常巧妙,它们不仅仅是检验你是否记住了公式,更多的是引导你去思考如何在实际的计算场景中运用这种代数思维来优化性能和代码结构。
评分 评分 评分 评分 评分本站所有内容均为互联网搜索引擎提供的公开搜索信息,本站不存储任何数据与内容,任何内容与数据均与本站无关,如有需要请联系相关搜索引擎包括但不限于百度,google,bing,sogou 等
© 2026 book.quotespace.org All Rights Reserved. 小美书屋 版权所有