Building Computer Vision Projects with OpenCV 4 and C++

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithmsKey FeaturesDiscover best practices for engineering and maintaining OpenCV projectsExplore important deep learning tools for image classificationUnderstand basic image matrix formats and filtersBook DescriptionOpenCV 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 EscriváLearn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá Vinícius G. Mendonça and Prateek JoshiWhat you will learnStay up-to-date with algorithmic design approaches for complex computer vision tasksWork with OpenCV's most up-to-date API through various projectsUnderstand 3D scene reconstruction and Structure from Motion (SfM)Study camera calibration and overlay augmented reality (AR) using the ArUco moduleCreate CMake scripts to compile your C++ applicationExplore segmentation and feature extraction techniquesRemove backgrounds from static scenes to identify moving objects for surveillanceWork with new OpenCV functions to detect and recognize text with TesseractWho this book is forIf 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. About the Author 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 an artificial intelligence researcher an author of several books and a TEDx speaker. He has been featured in Forbes 30 Under 30 CNBC TechCrunch Silicon Valley Business Journal and many more publications. He is the founder of Pluto AI a venturefunded Silicon Valley start-up building an intelligence platform for water facilities. He graduated from the University of Southern California with a Master's degree specializing in Artificial Intelligence. He has previously worked at NVIDIA and Microsoft Research.Vinícius G. Mendonça is a computer graphics university professor at Pontifical Catholic University of Paraná (PUCPR). He