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Mastering OpenCV 4

You're reading from   Mastering OpenCV 4 A comprehensive guide to building computer vision and image processing applications with C++

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Product type Paperback
Published in Dec 2018
Publisher
ISBN-13 9781789533576
Length 280 pages
Edition 3rd Edition
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Authors (2):
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Roy Shilkrot Roy Shilkrot
Author Profile Icon Roy Shilkrot
Roy Shilkrot
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Toc

Table of Contents (12) Chapters Close

Preface 1. Cartoonifier and Skin Color Analysis on the RaspberryPi 2. Explore Structure from Motion with the SfM Module FREE CHAPTER 3. Face Landmark and Pose with the Face Module 4. Number Plate Recognition with Deep Convolutional Networks 5. Face Detection and Recognition with the DNN Module 6. Introduction to Web Computer Vision with OpenCV.js 7. Android Camera Calibration and AR Using the ArUco Module 8. iOS Panoramas with the Stitching Module 9. Finding the Best OpenCV Algorithm for the Job 10. Avoiding Common Pitfalls in OpenCV 11. Other Books You May Enjoy

Facial landmark detection in OpenCV

Landmark detection starts with face detection, finding faces in the image and their extents (bounding boxes). Facial detection has long been considered a solved problem, and OpenCV contains one of the first robust face detectors freely available to the public. In fact, OpenCV, in its early days, was majorly known and used for its fast face detection feature, implementing the canonical Viola-Jones boosted cascade classifier algorithm (Viola et al. 2001, 2004), and providing a pre-trained model. While face detection has grown much since those early days, the fastest and easiest method for detecting faces in OpenCV is still to use the bundled cascade classifiers, by means of the cv::CascadeClassifier class provided in the core module.

We implement a simple helper function to detect faces with the cascade classifier, shown as follows:

void faceDetector...
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