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

Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision algorithms and explore deep learning and face detection
Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision algorithms and explore deep learning and face detection by David Millan Escriva
English | 2019 | ISBN: 1838644673 | 538 Pages | EPUB | 221 MB

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

  • Mastering OpenCV 4 – Third Edition by Roy Shilkrot and David Millan Escriva
  • Learn OpenCV 4 By Building Projects – Second Edition by David Millan Escriva, Vinicius G. Mendonca, 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