Bradski Gary - Learning Opencv 3: Computer Vision in C++ with the Opencv Library

• 2016-12-09: First Release
• 2017-01-20: Second Release
• 2017-12-15: Third Release

Computer vision is a rapidly growing field largely because of four trends:

• The advent of mobile phones put millions of cameras in peoples hands.

• The Internet and search engines aggregated the resulting giant flows of image and video data into huge databases.

• Computer processing power became a cheap commodity.

• Vision algorithms themselves became more mature (now with the advent of deep neural networks, which OpenCV is increasingly supporting; see dnn at ]).

OpenCV has played a role in the growth of computer vision by enabling hundreds of thousands of people to do more productive work in vision. OpenCV 3.x now allows students, researchers, professionals, and entrepreneurs to efficiently implement projects and jump-start research by providing them with a coherent C++ computer vision architecture that is optimized over many platforms.

The purpose of this book is to:

• Comprehensively document OpenCV by detailing what function calling conventions really mean and how to use them correctly

• Give the reader an intuitive understanding of how the vision algorithms work

• Give the reader some sense of what algorithm to use and when to use it

• Give the reader a boost in implementing computer vision and machine learning algorithms by providing many working code examples to start from

• Suggest ways to fix some of the more advanced routines when something goes wrong

This book documents OpenCV in a way that allows the reader to rapidly do interesting and fun things in computer vision. It gives an intuitive understanding of how the algorithms work, which serves to guide the reader in designing and debugging vision applications and also makes the formal descriptions of computer vision and machine learning algorithms in other texts easier to comprehend and remember.