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Mastering OpenCV 4

Mastering OpenCV 4

By : Roy Shilkrot, Millán Escrivá
2.7 (3)
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Mastering OpenCV 4

Mastering OpenCV 4

2.7 (3)
By: Roy Shilkrot, Millán Escrivá

Overview of this book

Mastering OpenCV, now in its third edition, 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. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.
Table of Contents (12 chapters)
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Face Detection and Recognition with the DNN Module

In this chapter, we are going to learn the main techniques of face detection and recognition. Face detection is the process whereby faces are located in a whole image. In this chapter, we are going to cover different techniques to detect faces in images, from classic algorithms using cascade classifiers with Haar features to newer techniques using deep learning. Face recognition is the process of identifying a person that appears in an image. We are going to cover the following topics in this chapter:

  • Face detection with different methods
  • Face preprocessing
  • Training a machine learning algorithm from collected faces
  • Face recognition
  • Finishing touches
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