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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

David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Ebook
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
  • 1. Getting Started with OpenCV
  • 2. An Introduction to the Basics of OpenCV
  • 3. Learning Graphical User Interfaces
  • 4. Delving into Histogram and Filters
  • 5. Automated Optical Inspection, Object Segmentation, and Detection
  • 6. Learning Object Classification
  • 7. Detecting Face Parts and Overlaying Masks
  • 8. Video Surveillance, Background Modeling, and Morphological Operations
  • 9. Learning Object Tracking
  • 10. Developing Segmentation Algorithms for Text Recognition
  • 11. Text Recognition with Tesseract
  • 12. Deep Learning with OpenCV
  • 13. Cartoonifier and Skin Color Analysis on the RaspberryPi
  • 14. Explore Structure from Motion with the SfM Module
  • 15. Face Landmark and Pose with the Face Module
  • 16. Number Plate Recognition with Deep Convolutional Networks
  • 17. Face Detection and Recognition with the DNN Module
  • 18. Android Camera Calibration and AR Using the ArUco Module
  • 19. iOS Panoramas with the Stitching Module
  • 20. Finding the Best OpenCV Algorithm for the Job
  • 21. Avoiding Common Pitfalls in OpenCV
  • Title: Building Computer Vision Projects with OpenCV 4 and C++. Implement complex computer vision algorithms and explore deep learning and face detection
  • Author: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
  • Original title: Building Computer Vision Projects with OpenCV 4 and C++. Implement complex computer vision algorithms and explore deep learning and face detection
  • ISBN: 9781838644673, 9781838644673
  • Date of issue: 2019-03-26
  • Format: Ebook
  • Item ID: e_14s4
  • Publisher: Packt Publishing