作者：AdrianKaehler，Gary
页数：2册(25,14,9
出版社：东南大学出版社
出版日期：2017
ISBN：9787564173548
电子书格式：pdf/epub/txt
内容简介
本书将你置身于迅速发展的计算机视觉领域。本书作者是免费开源OpenCV的发起人，这本书为你介绍了计算机视觉，例证了如何迅速建立使计算机能“看”的应用程序，以及如何基于计算机获取的数据作出决策。
作者简介
Adrian Kaehlef是一位企业家，同时也是Silicon Valley Deep Learnlng Group的创始人。其工作包括机器学习、统计建模、计算机视觉以及机器人学。他在斯坦福大学AI实验室拥有职位，另外还是DARPA Grand Challerige竞赛获胜团队Stanley的其中一员。
本书特色
本书将你置身于迅速发展的计算机视觉领域。本书作者是免费开源OpenCV的发起人，这本书为你介绍了计算机视觉，例证了如何迅速建立使计算机能“看”的应用程序，以及如何基于计算机获取的数据作出决策。
目录
Preface1. 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 Exercises2. 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 Exercises3. 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 Exercises4. 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 Exercises5. Array Operati0ns More Things You Can Do with Arrays cv::abs0 cv::absdiff() cv::add0 cv::addWeighted() cv::bitwise_and() ……
6. Drawing and Annotating7. Functors in OpenCV8. Image, Video, and Data Files9. Cross-Platform and Native Windows10. Filters and Convolution11. General Image Transforms12. Image Analysis13. Histograms and Templates14. Contours15. Background Subtraction16. Keypoints and Descriptors17. Tracking18. Camera Models and Calibration19. Projection and Three-Dimensional Vision20. The Basics of Machine Learning in OpenCV21. StatModel: The Standard Model for Learning in OpenCV22. Object Detection23. Future of OpenCVA. Planar SubdivisionsB. opencv_contribC. Calibration PatternsBibliographyIndex
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 Exercises2. 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 Exercises3. 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 Exercises4. 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 Exercises5. Array Operati0ns More Things You Can Do with Arrays cv::abs0 cv::absdiff() cv::add0 cv::addWeighted() cv::bitwise_and() ……
6. Drawing and Annotating7. Functors in OpenCV8. Image, Video, and Data Files9. Cross-Platform and Native Windows10. Filters and Convolution11. General Image Transforms12. Image Analysis13. Histograms and Templates14. Contours15. Background Subtraction16. Keypoints and Descriptors17. Tracking18. Camera Models and Calibration19. Projection and Three-Dimensional Vision20. The Basics of Machine Learning in OpenCV21. StatModel: The Standard Model for Learning in OpenCV22. Object Detection23. Future of OpenCVA. Planar SubdivisionsB. opencv_contribC. Calibration PatternsBibliographyIndex
