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Learning OpenCV3 Computer Vision in C++ with the OpenCV Library.pdf

2016-12-23 上传大小:42.56MB
Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a tho
rough introduction for developers, academics, roboticists, and hobbyists. You’ll learn what it takes to build applications that enable computers to "see" and make decisions based on that data.



Title: Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library
Author: Adrian Kaehler, Gary Bradski
Length: 1024 pages
Edition: 1
Language: English
Publisher: O'Reilly Media
Publication Date: 2017-01-08
ISBN-10: 1491937998
ISBN-13: 9781491937990

With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you’ve learned.

This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision.

Learn OpenCV data types, array types, and array operations
Capture and store still and video images with HighGUI
Transform images to stretch, shrink, warp, remap, and repair
Explore pattern recognition, including face detection
Track objects and motion through the visual field
Reconstruct 3D images from stereo vision
Discover basic and advanced machine learning techniques in OpenCV
Table of Contents
Chapter 1. Overview
Chapter 2. Introduction to OpenCV
Chapter 3. Getting to Know OpenCV Data Types
Chapter 4. Images and Large Array Types
Chapter 5. Array Operations
Chapter 6. Drawing and Annotating
Chapter 7. Functors in OpenCV
Chapter 8. Image, Video, and Data Files
Chapter 9. Cross-Platform and Native Windows
Chapter 10. Filters and Convolution
Chapter 11. General Image Transforms
Chapter 12. Image Analysis
Chapter 13. Histograms and Templates
Chapter 14. Contours
Chapter 15. Background Subtraction
Chapter 16. Keypoints and Descriptors
Chapter 17. Tracking
Chapter 18. Camera Models and Calibration
Chapter 19. Projection and Three-Dimensional Vision
Chapter 20. The Basics of Machine Learning in OpenCV
Chapter 21. StatModel: The Standard Model for Learning in OpenCV
Chapter 22. Object Detection
Chapter 23. Future of OpenCV
Appendix A. Planar Subdivisions
Appendix B. opencv_contrib
Appendix C. Calibration Patterns
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评论共有7条

name
luohuiwu2017-09-24 11:51:31
部分页数没有内容
name
sandacn2017-09-14 08:53:07
这本书非常稀缺,建议下载
name
jsho0002017-03-30 17:06:13
非常新, 很棒. 這正是我想要的.
name
qq_168372292017-02-22 17:36:19
非常棒,是最新版的,而且章节完整,很喜欢,谢谢!
name
u0118503202017-01-25 01:03:03
非常感谢,这就是新版的pdf。
name
beskcom2017-01-20 17:47:16
非常棒的资料!谢谢!
name
zzr5252016-12-30 14:23:12
不错的资源,就是部分页数没有内容。例如内容248页(274/1018)

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