Video Description
OpenCV 3 is a native cross-platform C++ Library for computer vision, machine learning, and image processing. This impressive API also makes starting OpenCV 3 projects a daunting prospect. Each video in this course provides a practical and innovative approach so youβll be able to choose wisely in your future projects. It will help you tackle increasingly challenging computer vision problems that you may face in your career. Each of the examples have been battle-tested in the authorβs industry research.
Youβll deep dive into video surveillance tools, such as wildlife camera traps, extreme sports cameras, and closed circuit video cameras. Many applications require video content analysis, so youβll learn about video stabilization, background video monitoring, and subtraction. Moving ahead, youβll find out about object detection robot vision, where youβll match image descriptors. Youβll also get an overview of image warping and the perspective transform, and will use homographies to warp images.
Finally, explore into Artificial Intelligence with Deep Neural Networks and youβll get a taste of how DNNs can be used within OpenCV. Youβll see how to install and load DNN models and classify images. At the end of the course, youβll discover how to convert low-level pixel information to high-level concepts for applications such as object detection, recognition, and scene monitoring.
Style and Approach
These videos show you computer vision applications in a step-by-step manner. Practical end-to-end projects cover the important computer vision problems, and each project shows how OpenCV3 is used within a specific goal-oriented context. Youβll get a walkthrough of several projects from the concept and approach through to an efficient implementation with OpenCV 3.