计算机视觉：一种现代的方法

计算机视觉：一种现代的方法【计算机视觉：一种现代的方法】《计算机视觉：一种现代的方法》是2004年清华大学出版社出版的图书，作者是Forsyth, Ponce 。
基本介绍书名：计算机视觉：一种现代的方法
作者：Forsyth, Ponce
ISBN：9787302077954
定价：65元
出版社：清华大学出版社
出版时间：2004.02.01
内容简介本书是由计算机视觉领域的两位权威专家编写的，全面介绍了现代计算机视觉的各种研究方法。本书不仅系统阐述了计算机视觉的原理与方法，而且还给出了很多有用的资料，如伪代码、工作範例、练习以及编程作业等，以助于读者创建自己的应用程式。通过本书的学习，读者可以掌握来自作者第一手的计算机处理视觉技术以及大量的数学方法。本书是计算机科学、计算机工程及电子工程高年级本科生和研究生“计算机视学”的很好教材，也是从事计算机视觉研究人员的重要参考书。目录Part I Image Formation and Image Models1 CAMERAS1.1 Pinhole Cameras1.1.1 Perspective Projection1.1.2 Affine Projection1.2 Cameras with Lenses1.2.1 Paraxial Geometric Optics1.2.2 Thin Lenses1.2.3 Real Lenses1.3 The Human Eye1.4 Sensing1.4.1 CCD Cameras1.4.2 Sensor Models1.5 NotesProblems2 GEOMETRIC CAMERA MODELS2.1 Elements of analytical Euclidean Geometry2.1.1 Coordinate Systems and Homogeneous Coordinates2.1.2 Coordinate System Changes and Rigid Transformations2.2 Camera Parameters and the Perspective Projection2.2.1 Intrinsic Parameters2.2.2 Extrinsic Parameters2.2.3 A Characterization of Perspective Projection Matrices2.3 Affine Cameras and Affine Projection Equations2.3.1 Affine Cameras2.3.2 Affine Projection Equations2.3.3 A Characterization of Affine Projection Matrices2.4 NotesProblems3 GEOMETRIC CAMERA CALIBRATION3.1 Least-Squares Parameter Estimation3.1.1 Linear Least-Squares Methods3.1.2 Nonlinear Least-Squares Methods3.2 A Linear Approach to Camera Calibration3.2.1 Estimation of the Projection Matrix3.2.2 Estimation of the Intrinsic and Extrinsic Parameters3.2.3 Degenerate Point Configurations3.3 Taking Radial Distortion into Account3.3.1 Estimation of the Projection Matrix3.3.2 Estimation of the Intrinsic and Extrinsic Parameters3.3.3 Degenerate Point Configurations3.4 Analytical Photogrammetry3.5 An Application:Mobile Robot Localization3.6 NotesProblems4 RADIOMETRY-MEASURING LIGHT4.1 Light in Space4.1.1 Foreshortening4.1.2 Solid Angle4.1.3 Radiance4.2 Light at Surfaces4.2.1 Simplifying Assumptions4.2.2 The Bidirectional Reflectance Distribution Function4.2.3 Example:The Radiometry of Thin Lenses4.3 Important Special Cases4.3.1 Radiosity4.3.2 directional Hemispheric Reflectance4.3.3 Lambertian Surfaces and Albedo4.3.4 Specular Surfaces4.3.5 The Lambertian+Specular Model4.4 NotesProblems5 SOURCES,SHADOWS,AND SHADING6 COLORPart II Early Vision:Just One Image7 LINEAR FILTERS8 EDGE DETECTION9 TEXTUREPart III Early Vision:Multiple Images10 THE GEOMETRY OF MULTIPLE VIEWS11 STEREOPSIS12 AFFINE STRUCTURE FROM MOTION13 PROJECTIVE STRUCTURE FROM MOTIONPart IV Mid-Level Vision14 SEGMENTATION BY CLUSTERING15 SEGMENTATION BY FITTING A MODEL16 SEGMENTATION AN FITTING USING PROBABILISTIC METHODS17 TRACKING WITH LINEAR DYNAMIC MODELSPart Ⅴ High-Level Vision:Geometric MethodsPart Ⅵ High-Level Vision:Probabilistic and Inferential MethodsPart Ⅶ ApplicationsBIBLIOGRAPHYINDEX