Face Recognition with OpenCV

Lenka Ptackova

VISGRAF - IMPA

Introduction

Face recognition is a biometric identification by scanning aperson’s face and matching it against a library of known faces.1

1The Free Dictionary

Overview

Uses

Video-based Face RecognitionFace Detection with OpenCVFace TrackingFace Recognition

My Application - FaceRec

Uses

Face recognition systems areused in:

I security and othersurveillance systems,

I photo collections -Facebook, iPhoto, Picasa,Windows Live PhotoGallery, etc.

I other apps - personalizedmarketing, Kinect,analyzing emotions,gender recognition, etc. Figure: MyHeritage Celebrity Look-Alikes

Uses

Figure: Imagus Technology on YouTube

Video-based Face Recognition

An optimal video-based face recognition system consists of:

I Face detection.

I Face tracking.

I Face recognition.

Face Detection with OpenCV

For face detection, OpenCV offers two types of cascadeclassifiers:

I Haar-Cascades (based on Haar-based cascade classifierinvented by Viola and Jones, 2002),

I LBP-Cascades (based on work by Ahonen, Hadid andPietikainen, 2006).

These trained classifiers include detectors of face, eyes, nose,whole body, etc.

Face Tracking

Face tracking is widely used in game or movie industry.OpenCV offers implementations of several algorithms formotion analysis and object tracking, such as CAMshift orLucas-Kanade feature tracker algorithm.

Figure: Avatar, 2009

Face Recognition

OpenCV 2.4 or higher comes with FaceRecognizer class forface recognition. There are three available algorithms:

I Eigenfaces.

I Fisherfaces.

I Local Binary Patterns Histograms.

In general, successful face recognition depends on:

I satisfactory image dataset,

I external conditions (light, quality of video).

FaceRec app

The application is based on Chapter 8 of Mastering OpenCVwith Practical Computer Vision Projects [Emami, 2012].FaceRec app does:

I collecting faces,

I training of recognizer,

I face recognition.

Collecting Faces

Training

Face Recognition

Comments

I Eigenfaces algorithm worked better.

I Tested only in constrained setting.

I It is fast enough.

I Logitech HD 720p worked much better than Microsoft1080p HD camera.

I One limitation is face detection.

I Does not perform proper face tracking.

References

Accelerating Face-in-the-Crowd Recognition with GPU Technology,webinar at GTC Express. November 5th, 2013.

IMAGUS TECHNOLOGY PTY LTD, url =”http://www.imagus.com.au/”

MyHeritage Celebrity Look-Alikes, url =”http://celebridades.myheritage.com.br/celebrity-look-alikes”

Shervin Emami. ”Face Recognition using Eigenfaces or Fisherfaces”in Mastering OpenCV with Practical Computer Vision Projects. PactPublishing, 2012. ISBN 1849517827.

References

Ahonen T, Hadid A, Pietikainen M (2006), Face description withlocal binary patterns: application to face recognition. IEEETransactions on Pattern Analysis and Machine Intelligence,28(12):2037-2041.

Viola, Jones: Robust Real-time Object Detection, IJCV 2001.