3D计算机视觉:原理、算法及应用

3D计算机视觉:原理、算法及应用
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作者:
2021-09
版次: 1
ISBN: 9787121419508
定价: 149.00
装帧: 其他
页数: 408页
  • 本书主要内容围绕3D 计算机视觉展开,介绍了相关的基础概念、基本原理、典型算法、实用技术和应用成果。本书可在学过其姊妹篇《2D 计算机视觉:原理、算法及应用》后学习。 本书将从客观场景出发到后对场景进行理解的全过程分为5 个部分进行介绍。第1 部分是图像采集,介绍了摄像机标定和3D 图像采集技术;第2 部分是视频运动,介绍了视频图像和运动信息,以及对运动目标进行检测和跟踪的技术;第3 部分是物体重建,介绍了双目立体视觉和单目图像恢复技术;第4 部分是物体分析,介绍了3D 目标表达和广义匹配;第5 部分是高层理解,介绍了知识和场景解释及时空行为理解。本书除提供大量示例外,还针对每章的内容提供了自我检测题(含提示并附有答案),并且给出了相关的参考文献和术语索引(包括英文)。 章毓晋,于1989年获比利时列日大学应用科学博士学位。1989—1993年,先后在荷兰德尔夫特大学从事博士后研究工作并担任专职研究员。于1993年到清华大学任教,1997年被聘为教授,1998年被聘为博士生导师,2014年成为教学科研系列长聘教授。在2003年学术休假期间,同时被聘为新加坡南洋理工大学访问教授。在清华大学,先后开出并讲授10多门本科生和研究生课程。在南洋理工大学,开出并讲授研究生课程“现代图像分析(英语)”。已编写出版了图像工程系列教材第1版、第2版、第3版和第4版,《图像工程问题解析》、《图像处理和分析基础》、《图像处理和分析技术》(第2版和第3版)、《图像处理和分析教程》(第1版、第2版和第3版)、《计算机视觉教程》(第1版、第2版和第3版)和《图像处理基础教程》,以及Image Engineering: Processing, Analysis, and Understanding,Image Engineering, Vol.1, Image Processing,Image Engineering, Vol.2, Image Analysis,Image Engineering, Vol.3, Image Understanding,翻译出版了《彩色数字图像处理》、《图像处理基础》(第2版)、《MATLAB图像和视频处理》、《计算机视觉基础》和《彩色计算机视觉》,研制出版了《“图像处理和分析’’多媒体计算机辅助教学课件》和《图像处理和分析网络课程》。已在国内外发表了30多篇教学研究论文。主要科学研究领域为所提出的图像工程(图像处理、图像分析、图像理解及其技术应用)。自1996年起,已连续26年对中国图像工程的研究及主要文献进行了系统的年度分类和总结综述。已在国内外发表了500多篇图像工程研究论文,出版了专著《图象分割》《基于内容的视觉信息检索》《基于子空间的人脸识别》,编著了《英汉图像工程辞典》(第1版、第2版和第3版)、《图像工程技术选编》和《图像工程技术选编(二)》,主持编著了Advances in Image and Video Segmentation,Semantic-Based Visual Information Retrieval,Advances in Face Image Analysis: Techniques and Technologies,出版了Handbook of Image Engineering和A Selection of Image Processing Techniques.曾任第24届国际图像处理学术会议(ICIP‘2017)等20多个国内外学术会议的程序委员会主席。现为中国图象图形学学会名誉监事长和会士、国际电气电子工程师协会(IEEE)高级会员、国际光学工程协会(SPIE)会士(因在图像工程方面的成就)。 第1 章计算机视觉概述·····································································.1

    1.1 人类视觉及特性····································································.1

    1.1.1 视觉特点····································································.2

    1.1.2 视觉的亮度特性···························································.3

    1.1.3 视觉的空间特性···························································.5

    1.1.4 视觉的时间特性···························································.6

    1.1.5 视知觉·······································································.8

    1.2 计算机视觉理论和框架··························································.10

    1.2.1 计算机视觉的研究目的、任务和方法·······························.11

    1.2.2 视觉计算理论·····························································.11

    1.2.3 框架问题和改进··························································.16

    1.3 3D 视觉系统和图像技术·························································.18

    1.3.1 3D 视觉系统流程·························································.18

    1.3.2 计算机视觉和图像技术层次···········································.19

    1.3.3 图像技术类别·····························································.20

    1.4 本书结构框架和内容概况·······················································.21

    1.4.1 结构框架和主要内容····················································.22

    1.4.2 各章概况···································································.22

    1.5 各节要点和进一步参考··························································.23

    第2 章摄像机标定···········································································25

    2.1 线性摄像机模型···································································.25

    2.1.1 完整成像模型·····························································.26

    2.1.2 基本标定程序·····························································.27

    2.1.3 内、外参数································································.28

    2.2 非线性摄像机模型································································.30

    2.2.1 畸变类型···································································.31

    2.2.2 标定步骤···································································.33

    2.2.3 标定方法分类·····························································.34

    2.3 传统标定方法······································································.35

    2.3.1 基本步骤和参数··························································.36

    2.3.2 两级标定法································································.36

    2.3.3 精度提升···································································.40

    2.4 自标定方法·········································································.41

    2.5 各节要点和进一步参考··························································.44

    第3 章 3D 图像采集··········································································45

    3.1 高维图像············································································.45

    3.2 深度图···············································································.46

    3.2.1 深度图和灰度图像·······················································.47

    3.2.2 本征图像和非本征图像·················································.47

    3.2.3 深度成像方式·····························································.49

    3.3 直接深度成像······································································.50

    3.3.1 飞行时间法································································.50

    3.3.2 结构光法···································································.53

    3.3.3 莫尔等高条纹法··························································.55

    3.3.4 同时采集深度和亮度图像··············································.58

    3.4 立体视觉成像······································································.59

    3.4.1 双目横向模式·····························································.59

    3.4.2 双目会聚横向模式·······················································.63

    3.4.3 双目轴向模式·····························································.65

    3.5 各节要点和进一步参考··························································.67

    第4 章视频图像和运动信息·······························································69

    4.1 视频基础············································································.70

    4.1.1 视频表达和模型··························································
  • 内容简介:
    本书主要内容围绕3D 计算机视觉展开,介绍了相关的基础概念、基本原理、典型算法、实用技术和应用成果。本书可在学过其姊妹篇《2D 计算机视觉:原理、算法及应用》后学习。 本书将从客观场景出发到后对场景进行理解的全过程分为5 个部分进行介绍。第1 部分是图像采集,介绍了摄像机标定和3D 图像采集技术;第2 部分是视频运动,介绍了视频图像和运动信息,以及对运动目标进行检测和跟踪的技术;第3 部分是物体重建,介绍了双目立体视觉和单目图像恢复技术;第4 部分是物体分析,介绍了3D 目标表达和广义匹配;第5 部分是高层理解,介绍了知识和场景解释及时空行为理解。本书除提供大量示例外,还针对每章的内容提供了自我检测题(含提示并附有答案),并且给出了相关的参考文献和术语索引(包括英文)。
  • 作者简介:
    章毓晋,于1989年获比利时列日大学应用科学博士学位。1989—1993年,先后在荷兰德尔夫特大学从事博士后研究工作并担任专职研究员。于1993年到清华大学任教,1997年被聘为教授,1998年被聘为博士生导师,2014年成为教学科研系列长聘教授。在2003年学术休假期间,同时被聘为新加坡南洋理工大学访问教授。在清华大学,先后开出并讲授10多门本科生和研究生课程。在南洋理工大学,开出并讲授研究生课程“现代图像分析(英语)”。已编写出版了图像工程系列教材第1版、第2版、第3版和第4版,《图像工程问题解析》、《图像处理和分析基础》、《图像处理和分析技术》(第2版和第3版)、《图像处理和分析教程》(第1版、第2版和第3版)、《计算机视觉教程》(第1版、第2版和第3版)和《图像处理基础教程》,以及Image Engineering: Processing, Analysis, and Understanding,Image Engineering, Vol.1, Image Processing,Image Engineering, Vol.2, Image Analysis,Image Engineering, Vol.3, Image Understanding,翻译出版了《彩色数字图像处理》、《图像处理基础》(第2版)、《MATLAB图像和视频处理》、《计算机视觉基础》和《彩色计算机视觉》,研制出版了《“图像处理和分析’’多媒体计算机辅助教学课件》和《图像处理和分析网络课程》。已在国内外发表了30多篇教学研究论文。主要科学研究领域为所提出的图像工程(图像处理、图像分析、图像理解及其技术应用)。自1996年起,已连续26年对中国图像工程的研究及主要文献进行了系统的年度分类和总结综述。已在国内外发表了500多篇图像工程研究论文,出版了专著《图象分割》《基于内容的视觉信息检索》《基于子空间的人脸识别》,编著了《英汉图像工程辞典》(第1版、第2版和第3版)、《图像工程技术选编》和《图像工程技术选编(二)》,主持编著了Advances in Image and Video Segmentation,Semantic-Based Visual Information Retrieval,Advances in Face Image Analysis: Techniques and Technologies,出版了Handbook of Image Engineering和A Selection of Image Processing Techniques.曾任第24届国际图像处理学术会议(ICIP‘2017)等20多个国内外学术会议的程序委员会主席。现为中国图象图形学学会名誉监事长和会士、国际电气电子工程师协会(IEEE)高级会员、国际光学工程协会(SPIE)会士(因在图像工程方面的成就)。
  • 目录:
    第1 章计算机视觉概述·····································································.1

    1.1 人类视觉及特性····································································.1

    1.1.1 视觉特点····································································.2

    1.1.2 视觉的亮度特性···························································.3

    1.1.3 视觉的空间特性···························································.5

    1.1.4 视觉的时间特性···························································.6

    1.1.5 视知觉·······································································.8

    1.2 计算机视觉理论和框架··························································.10

    1.2.1 计算机视觉的研究目的、任务和方法·······························.11

    1.2.2 视觉计算理论·····························································.11

    1.2.3 框架问题和改进··························································.16

    1.3 3D 视觉系统和图像技术·························································.18

    1.3.1 3D 视觉系统流程·························································.18

    1.3.2 计算机视觉和图像技术层次···········································.19

    1.3.3 图像技术类别·····························································.20

    1.4 本书结构框架和内容概况·······················································.21

    1.4.1 结构框架和主要内容····················································.22

    1.4.2 各章概况···································································.22

    1.5 各节要点和进一步参考··························································.23

    第2 章摄像机标定···········································································25

    2.1 线性摄像机模型···································································.25

    2.1.1 完整成像模型·····························································.26

    2.1.2 基本标定程序·····························································.27

    2.1.3 内、外参数································································.28

    2.2 非线性摄像机模型································································.30

    2.2.1 畸变类型···································································.31

    2.2.2 标定步骤···································································.33

    2.2.3 标定方法分类·····························································.34

    2.3 传统标定方法······································································.35

    2.3.1 基本步骤和参数··························································.36

    2.3.2 两级标定法································································.36

    2.3.3 精度提升···································································.40

    2.4 自标定方法·········································································.41

    2.5 各节要点和进一步参考··························································.44

    第3 章 3D 图像采集··········································································45

    3.1 高维图像············································································.45

    3.2 深度图···············································································.46

    3.2.1 深度图和灰度图像·······················································.47

    3.2.2 本征图像和非本征图像·················································.47

    3.2.3 深度成像方式·····························································.49

    3.3 直接深度成像······································································.50

    3.3.1 飞行时间法································································.50

    3.3.2 结构光法···································································.53

    3.3.3 莫尔等高条纹法··························································.55

    3.3.4 同时采集深度和亮度图像··············································.58

    3.4 立体视觉成像······································································.59

    3.4.1 双目横向模式·····························································.59

    3.4.2 双目会聚横向模式·······················································.63

    3.4.3 双目轴向模式·····························································.65

    3.5 各节要点和进一步参考··························································.67

    第4 章视频图像和运动信息·······························································69

    4.1 视频基础············································································.70

    4.1.1 视频表达和模型··························································
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