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Learning OpenCV 4 Computer Vision with Python 3

You're reading from   Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789531619
Length 372 pages
Edition 3rd Edition
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Authors (2):
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Joe Minichino Joe Minichino
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Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (13) Chapters Close

Preface 1. Setting Up OpenCV 2. Handling Files, Cameras, and GUIs FREE CHAPTER 3. Processing Images with OpenCV 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. Other Book You May Enjoy Appendix A: Bending Color Space with the Curves Filter

Summary

By now, you should have a good understanding of how face detection and face recognition work and how to implement them in Python and OpenCV 4.

Face detection and face recognition are constantly evolving branches of computer vision, with algorithms being developed continuously, and they will evolve even faster in the near future with a growing interest in robotics and the Internet of Things (IoT).

For now, the accuracy of detection and recognition algorithms heavily depends on the quality of the training data, so make sure you provide your applications with a large number of training images covering a variety of expressions, poses, and lighting conditions.

As human beings, we might be predisposed to think that human faces are particularly recognizable. We might even be overconfident in our own face recognition abilities. However, in computer vision, there is nothing very...

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