Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering OpenCV 4

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

Arrow left icon
Product type Paperback
Published in Dec 2018
Publisher
ISBN-13 9781789533576
Length 280 pages
Edition 3rd Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
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
Arrow right icon
View More author details
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

Summary

This chapter has shown you all the steps required to create a real-time face recognition application, with enough preprocessing to allow some differences between the training set conditions and the testing set conditions, just using basic algorithms. We used face detection to find the location of a face within the camera image, followed by several forms of face preprocessing to reduce the effects of different lighting conditions, camera and face orientations, and facial expressions.

We then trained an Eigenfaces or Fisherfaces machine learning system with the preprocessed faces we collected, and finally we performed face recognition to see who the person is with face verification, providing a confidence metric in case it is an unknown person.

Rather than providing a command-line tool that processes image files in an offline manner, we combined all the preceding steps into...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image