Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision algorithms and explore deep learning and face detection

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms

Key Features:

- Discover best practices for engineering and maintaining OpenCV projects

- Explore important deep learning tools for image classification

- Understand basic image matrix formats and filters

Book Description:

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation.

This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books:

- Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá

- Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi

What You Will Learn:

- Stay up-to-date with algorithmic design approaches for complex computer vision tasks

- Work with OpenCV s most up-to-date API through various projects

- Understand 3D scene reconstruction and Structure from Motion (SfM)

- Study camera calibration and overlay augmented reality (AR) using the ArUco module

- Create CMake scripts to compile your C++ application

- Explore segmentation and feature extraction techniques

- Remove backgrounds from static scenes to identify moving objects for surveillance

- Work with new OpenCV functions to detect and recognize text with Tesseract

Who this book is for:

If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.

David Millán Escrivá was 8 years old when he wrote his first program on an 8086 PC in Basic, which enabled the 2D plotting of basic equations. In 2005, he finished his studies in IT with honors, through the Universitat Politécnica de Valencia, in human-computer interaction supported by computer vision with OpenCV (v0.96). He has worked with Blender, an open source, 3D software project, and on its first commercial movie, Plumiferos, as a computer graphics software developer. David has more than 10 years' experience in IT, with experience in computer vision, computer graphics, pattern recognition, and machine learning, working on different projects, and at different start-ups, and companies. He currently works as a researcher in computer vision.

Prateek Joshi is the founder of Plutoshift and a published author of 9 books on Artificial Intelligence. He has been featured on Forbes 30 Under 30, NBC, Bloomberg, CNBC, TechCrunch, and The Business Journals. He has been an invited speaker at conferences such as TEDx, Global Big Data Conference, Machine Learning Developers Conference, and Silicon Valley Deep Learning. Apart from Artificial Intelligence, some of the topics that excite him are number theory, cryptography, and quantum computing. His greater goal is to make Artificial Intelligence accessible to everyone so that it can impact billions of people around the world.

Vinícius G. Mendonça is a professor at PUCPR and a mentor at Apple Developer Academy. He has a master's degree in Computer Vision and Image Processing (PUCPR) and a specialization degree in Game Development (Universidade Positivo). He is also one of the authors of the book Learn OpenCV 4 by Building Projects, also by Packt Publishing.He has been in this field since 1996. His former experience includes designing and programming a multithreaded framework for PBX tests at Siemens, coordination of Aurélio Dictionary software (including its apps for Android, IOS, and Windows phones), and coordination of an augmented reality educational activity for Positivo's Mesa Alfabeto, presented at CEBIT. Currently, he works with server-side Node.js at a company called Tenet Tech.