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玩转3D视界 —— 3D机器视觉及其应用

玩转3D视界 —— 3D机器视觉及其应用

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  • ISBN:9787121382581
  • 装帧:平装-胶订
  • 册数:暂无
  • 重量:暂无
  • 开本:24cm
  • 页数:12,278页
  • 出版时间:2020-02-01
  • 条形码:9787121382581 ; 978-7-121-38258-1

本书特色

3D 机器视觉是计算机视觉的重要组成部分。本书对3D 机器视觉的基础知识、核心算法及应用进行了系统、全面的介绍,具体包括3D 传感器、3D 数据表示、3D 数据存储与压缩、3D 数据处理、3D 几何测量与建模、3D 物体识别和3D 动作识别等。本书力求理论结合实际,在原理与概念讲解的基础上,辅以简单的应用实例,便于读者深刻地理解各部分的知识点并学以致用。为满足读者自检与思考的需要,书中给出了一些思考题,并列出了主要文献供读者参考。

内容简介

本书对3D机器视觉的基础知识、核心算法及其应用进行了系统和全面地介绍。具体包括3D传感器、3D数据表示、3D数据存储与压缩、3D数据处理、3D几何测量与建模、3D物体识别和3D动作识别等。本书力求理论结合实际, 在原理与概念讲解的基础上, 辅以简单的应用实例, 便于读者深刻地理解各部分的知识点, 学以致用。

目录

第1 章 引言·············································································································.1
1.1 何为“3D 视界”·······················································································.1
1.2 如何玩转3D 视界······················································································.2
1.3 本书的主要内容·························································································.4
1.3.1 章节内容························································································.4
1.3.2 应用介绍························································································.5
1.4 面向的读者································································································.6
第2 章 3D视界的硬实力与软实力——3D 相机与开发平台·······························.8
2.1 概述············································································································.8
2.2 双目相机··································································································.10
2.2.1 双目相机原理···············································································.10
2.2.2 立体匹配方法···············································································.13
2.3 结构光3D 相机························································································.17
2.3.1 结构光相机原理···········································································.17
2.3.2 结构光的分类···············································································.19
2.3.3 结构光的标定与匹配···································································.21
2.4 ToF 相机···································································································.24
2.4.1 ToF相机的发展历程和分类························································.25
2.4.2 ToF相机原理···············································································.26
2.4.3 ToF的标定与补偿·······································································.32
2.5 三种相机的对比及典型应用···································································.35
2.5.1 三种相机的对比···········································································.35
2.5.2 三种3D 相机的典型应用····························································.37
2.6 DMAPP 开发平台····················································································.42
2.6.1 SmartToF SDK——数据获取与处理···········································.43
2.6.2 DMAPP 架构················································································.47
2.6.3 DMAPP 的特点与优势································································.49
2.7 总结与思考······························································································.49
参考文献···········································································································.50
第3 章 3D数据表示方法·····················································································.51
3.1 概述··········································································································.51
3.2 深度图······································································································.52
3.3 点云··········································································································.55
3.3.1 点云概念介绍···············································································.55
3.3.2 点云数据获取···············································································.56
3.3.3 3D 相机数据与点云的转换·························································.58
3.3.4 点云数据分类及应用···································································.62
3.4 体素··········································································································.64
3.4.1 体素和体数据的概念···································································.64
3.4.2 点云的体素化···············································································.66
3.4.3 体素的应用场景···········································································.67
3.5 三角剖分··································································································.68
3.5.1 三角剖分的概念···
展开全部

作者简介

刘佩林,1965年9月生人,上海交通大学电子信息与电气工程学院教授,博士生导师。研究领域包括音视频、3D信号处理与智能分析;面向机器人的环境感知,人机交互,定位与导航;边缘计算等。自2017年起,任上海交通大学类脑智能应用技术研究中心主任。 应忍冬,1975年9月生人,上海交通大学电子信息与电气工程学院副教授,硕士生导师。研究领域包括嵌入式系统、数字信号处理及VLSI实现架构、人工智能领域的机器思维原理和实现。

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