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。 Gary Bradski是Arraiy.ai的CTO,曾在多家创业公司就职,另外还担任斯坦福大学AI实验室计算机科学系的咨询教授。作为OpenCV库的作者,他也是一位广受尊敬的发言人以及开源社区的贡献者。
无
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