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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 FREE CHAPTER 2. Explore Structure from Motion with the SfM Module 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

Estimating face direction from landmarks

Having obtained the facial landmarks, we can attempt to find the direction of the face. The 2D face landmark points essentially conform to the shape of the head. So, given a 3D model of a generic human head, we can find approximate corresponding 3D points for a number of facial landmarks, as shown in the following photo:

Estimated pose calculation

From these 2D–3D correspondences, we can calculate 3D pose (rotation and translation) of the head, with respect to the camera, by way of the Point-n-Perspective (PnP) algorithm. The details of the algorithm and object pose detection are beyond the scope of this chapter; however, we can quickly rationalize why just a handful of 2D&...

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