Duration

3 days

Outline

Topic 1 Overview of Face Recognition application

why does Face Recognition matter?

Applications of Face Recognition

Face Detection vs Face Recognition

Challenges in Face Recognition

Topic 2 Computer vision for Face Detection and Recognition

Data collection

Feature Extraction and Selection

Histogram of oriented gradients for face detection

Haar Feature-based Cascade Classifiers for face detection

Eigen Faces and Principal Component Analysis

Face Recognition Using Fisherface Method

Face Recognition using Local Binary Patterns Histograms

Topic 3 Overview of traditional machine learning algorithms

Machine Learning Pipeline

Machine learning algorithms for feature classification

Training machine learning models

Introduction to Neural Networks

Model Evaluation

Underfitting and Overfitting

Topic 4 Deep Learning Models

Fundamentals of Deep Learning

Training deep learning models and inference stage

Convolutional Neural Network

Face detection with deep learning

Multitask Cascaded Convolutional Neural Networks for face detection

Deep Learning based Face Recognition

Google FaceNet

VGGFace for face recognition

Topic 5 TensorFlow and OpenCV Frameworks

Facial landmark detector with dlib

keras-vggface

Face Recognition in OpenCV

Topic 6 practical examples

Face detection with MTCCN

face recognition with VGGFace

Age and gender detection

Programme scope, delivery arrangements and suitability are confirmed during enquiry.