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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
Languages
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
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

Detecting and Recognizing Faces

Computer vision makes many futuristic-sounding tasks a reality. Two such tasks are face detection (locating faces in an image) and face recognition (identifying a face as a specific person). OpenCV implements several algorithms for face detection and recognition. These have applications in all sorts of real-world contexts, from security to entertainment.

This chapter introduces some of OpenCV's face detection and recognition functionality, along with the data files that define particular types of trackable objects. Specifically, we look at Haar cascade classifiers, which analyze the contrast between adjacent image regions to determine whether or not a given image or sub image matches a known type. We consider how to combine multiple Haar cascade classifiers in a hierarchy so that one classifier identifies a parent region (for our purposes,...

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