This book targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks.

• Learn about the new features that help unlock the full potential of OpenCV 4
• Build face detection applications with a cascade classifier using face landmarks
• Create an optical character recognition (OCR) model using deep learning and convolutional neural networks

This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.

About the Authors

• Roy Shilkrot is an assistant professor of computer science at Stony Brook University, where he leads the Human Interaction group.
• David Millan Escriva was eight years old when he wrote his first program on an 8086 PC in Basic, which enabled the 2D plotting of basic equations.

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