收藏
Fundamentals of Computer Graphics, Fourth Edition - Steve Marschner, Peter Shirley

Fundamentals of Computer Graphics, Fourth Edition

Steve Marschner, Peter Shirley

出版社

A K Peters/CRC Press

出版时间

2015-12-18

ISBN

9781482229394

评分

★★★★★

标签

计算机图形学图形学Graphics计算机

书籍介绍
Drawing on an impressive roster of experts in the field, Fundamentals of Computer Graphics, Fourth Edition offers an ideal resource for computer course curricula as well as a user-friendly personal or professional reference. Focusing on geometric intuition, the book gives the necessary information for understanding how images get onto the screen by using the complementary approaches of ray tracing and rasterization. It covers topics common to an introductory course, such as sampling theory, texture mapping, spatial data structure, and splines. It also includes a number of contributed chapters from authors known for their expertise and clear way of explaining concepts. Highlights of the Fourth Edition Include: Updated coverage of existing topics Major updates and improvements to several chapters, including texture mapping, graphics hardware, signal processing, and data structures A text now printed entirely in four-color to enhance illustrative figures of concepts The fourth edition of Fundamentals of Computer Graphics continues to provide an outstanding and comprehensive introduction to basic computer graphic technology and theory. It retains an informal and intuitive style while improving precision, consistency, and completeness of material, allowing aspiring and experienced graphics programmers to better understand and apply foundational principles to the development of efficient code in creating film, game, or web designs.
AI导读
核心看点
  • 涵盖光线追踪与光栅化两大核心渲染技术
  • 深入讲解采样理论、纹理映射及空间数据结构
  • 强调几何直觉，清晰阐释图像生成底层原理
适合谁读
  • 计算机图形学初学者及高校相关专业学生
  • 从事游戏开发、渲染引擎研究的程序员
  • 希望系统掌握图形学基础理论的科研人员
读前提醒
  • 需具备扎实的线性代数基础以理解矩阵变换
  • 建议搭配GAMES101等课程视频辅助理解难点
  • 内容详实厚重，可结合红宝书互补阅读
读者共识
  • 图形学领域经典教材，内容全面且权威
  • 作者擅长化繁为简，概念解释清晰易懂
  • 部分章节细节繁琐，适合查阅参考而非通读

本导读基于书籍简介、目录、原文摘录、短评和书评生成，不等同于全文精读。

精彩摘录
  • "The principal difference is between a single rotation and two different orthogonal matrices. This difference causes another, less important, difference. Because the SVD has different singular vectors on the two sides, there is no need for negative Singular values: we can always flip the sign of a si"
  • "However, this type of transformation, in which one of the coordinates of the input vector appears in the denominator, can’t be achieved using affine transformations. We can allow for division with a simple generalization of the mechanism of homogeneous coordinates that we have been using for affine "
  • "Managing coordinate systems is one of the core tasks of almost any graphics program; key to this is managing orthonormal bases."
  • "The advantages of parallel projection are also its limitations. In our everyday experience (and even more so in photographs) objects look smaller as they get farther away, and as a result parallel lines receding into the distance do not ap- pear parallel. This is because eyes and cameras don’t colle"
  • "1.Rotate v_1 and v_2 to the x- and y-axes (the transform by R^T). 2.Scale in x and y by (λ_1,λ_2)(the transform by S). 3.Rotate the x- and y-axes back to v_1 and v_2 (the transform by R). Looking at the effect of these three transforms together, we can see that they have the effect of a nonuniform s"
  • "If you like to count dimensions: a symmetric 2×2 matrix has 3° of freedom, and the eigenvalue decomposition rewrites them as a rotation angle and two scale factors."
  • "A very similar kind of decomposition can be done with non symmetric matrices as well: it's the singular value decomposition(SVD), also discussed in section 6.4.1. The difference is that the matrices on either side of the dialogue matrix are no longer the same: A=USV^T The two orthogonal matrices tha"
  • "In summary, every matrix can be decomposed via SVD into a rotation times a scale times another rotation. Only symmetric matrices can be decomposed via eigenvalue diagonalization into a rotation times a scale times the inverse-rotation, and such matrices are a simple scale in an arbitrary direction. "
作者简介
I'm a Chicago transplant living in Salt Lake City, Utah. I have a physics degree from Reed College, but discovered computers when Professor Nicolas Wheeler forced me to do a ray tracing program in 1984. It was 2D ray tracing to do a caustic on a Vax and writing out the picture to a green Techtonix terminal. This convinced me to go to grad school in computer science at Illinois. I have been ray tracing ever since. I've done stints in various universities and companies and am currently in my own start-up company doing VR which is common but not using HMDs which is not!
用户评论
第4版前八章是基础的基础，图形领域从业人员都必须知道的，读完大致算入门了
很生动，就是太厚2333还没看完，印象最深的是讲硬件、重心坐标、光线追踪和光栅化的区别、流形、曲线还有画线算法等
太TM厚了，看得太累了
祖宗
行文略啰嗦，讲的偏数学／符号化，编程练习很少；用作“了解大图景的入门书”应该算是合适的。
我的笔记: https://max-young.github.io/computer_graphics/#/ 学习GAMES101时搭配着看的, GAMES101听不懂时会看这本书对应的章节, 能更加理解, 不然作业做不出来......
没读完
目前见过的最好的一本图形学教材，从线代、矩阵和视图的大幅数学基础入手，管线、信号、shader、mapping、sample等概念都花了巨额内容来解释。图形学入门我只推荐这一本书；并且原版书籍的英文并不难读，都是很清晰很直观的表达
A K Peters/CRC Press的其他书籍查看全部

收藏