学习OpenCV3（影印版 英文版 套装上下册） [Learning openCV 3]

《学习OpenCV3（影印版 英文版 套装上下册）》将带你进入计算机视觉这个快速扩展的领域。作为开源OpenCV库的作者，Aarian Kaehlier（艾德里安·克勒）和Gary Bradski（加里·布拉德斯基）为开发者、学术人员、机器人专家和爱好者全面介绍了OpenCV。你将学会如何构造出能够让计算机拥有“视觉”并根据数据作出决策的应用程序。
　　OpenCV拥有超过500个函数，涵盖了计算机视觉的多个方面，被广泛用于商业应用，如安全、医学成像、模式和面部识别、机器人学以及工厂产品检测。无论构建简单还是复杂的视觉应用，《学习OpenCV3（影印版 英文版 套装上下册）》都为你在计算机视觉和OpenCV方面奠定了坚实的基础。每章的习题有助于你学会运用所学到的知识。
　　书中涵盖了整个库，它全部是以现代C++来实现的，其中还包括用于计算机视觉的机器学习工具。

Preface
1． Overview
What Is OpenCV?
Who Uses OpenCV?
What Is Computer Vision?
The Origin of OpenCV
OpenCV Block Diagram
Speeding Up OpenCV with IPP
Who Owns OpenCV?
Downloading and Installing OpenCV
Installation
Getting the Latest OpenCV via Git
More OpenCV Documentation
Supplied Documentation
Online Documentation and the Wiki
OpenCV Contribution Repository
Downloading and Building Contributed Modules
Portability
Summary
Exercises

2． Introduction to 0penCV
Include Files
Resources
First Program——Display a Picture
Second Program——Video
Moving Around
A Simple Transformation
A Not-So-Simple Transformation
Input from a Camera
Writing to an AVI File
Summary
Exercises

3． Getting to Know OpenCV Data Types
The Basics
OpenCV Data Types
Overview of the Basic Types
Basic Types： Getting Down to Details
Helper Objects
Utility Functions
The Template Structures
Summary
Exercises

4． Images and Large Array Types
Dynamic and Variable Storage
The cv：：Mat Class： N-Dimensional Dense Arrays
Creating an Array
Accessing Array Elements Individually
The N-ary Array Iterator： NAryMatIterator
Accessing Array Elements by Block
Matrix Expressions： Algebra and cv：：Mat
Saturation Casting
More Things an Array Can Do
The cv：：SparseMat Class： Sparse Arrays
Accessing Sparse Array Elements
Functions Unique to Sparse Arrays
Template Structures for Large Array Types
Summary
Exercises

5． Array Operati0ns
More Things You Can Do with Arrays
cv：：abs0
cv：：absdiff（）
cv：：add0
cv：：addWeighted（）
cv：：bitwise_and（）
……
6． Drawing and Annotating
7． Functors in OpenCV
8． Image， Video， and Data Files
9． Cross-Platform and Native Windows
10． Filters and Convolution
11． General Image Transforms
12． Image Analysis
13． Histograms and Templates
14． Contours
15． Background Subtraction
16． Keypoints and Descriptors
17． Tracking
18． Camera Models and Calibration
19． Projection and Three-Dimensional Vision
20． The Basics of Machine Learning in OpenCV
21． StatModel： The Standard Model for Learning in OpenCV
22． Object Detection
23． Future of OpenCV
A． Planar Subdivisions
B． opencv_contrib
C． Calibration Patterns
Bibliography
Index