OpenCV is a native cross-platform C++ Library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for developing applications to process visual data such as photographs or videos. OpenCV has C++/C, Python, and Java interfaces with support for Windows, Linux, Mac, iOS, and Android, and offers extensive libraries with over 500 functions.
This video demonstrates how to develop a series of intermediate-to-advanced projects using OpenCV and Python, rather than teaching the core concepts of OpenCV in theoretical lessons. Instead, the working projects developed in this video teach the viewer how to apply their theoretical knowledge to topics such as image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization.
By the end of this video course, viewers will be OpenCV experts whose newly gained experience allows them to develop their own advanced computer vision applications.
About the Author
Riaz Munshi has a Bachelor's and a Master's degree in Computer Science from the University at Buffalo, NY. He is a computer vision and machine learning enthusiast. Riaz possess over three years' experience working on challenging problems in mobility, computing, and augmented reality. He has a solid foundation in Computer Science, with strong competencies in data structures, algorithms, and software design. Currently he is working at Yahoo as a Software Engineer, exploring use-cases that harness the power of AR in controlling robots. He makes robots perform more efficiently at their job by guiding them remotely via holograms.
