Real-Time Facial Recognition Using HOG Features
Updated 7 Dec 2020
This example demonstrates how to register a new face, label new face, extract features and recognise the face in real time.It is a very interesting topic. However, in this example, we are not particular in the accuracy, instead of that, i'm demonstrating the workflow. In order to increase the accuracy, we might need to extract more features for machine learning.
There are many examples available online, some links are provided below, you may take a look at their example.
Example 1: How to activate your webcam
Example 2 : Face Detection and Tracking Using Live Video Acquisition
Example 3: Code for Face Recognition with MATLAB Webinar
video : https://www.mathworks.com/videos/face-recognition-with-matlab-100902.html
Example 4 : Detecting Faces in Image
Example 5 : Facial Recognition using Kekre transform
Example 6 : Real-time Face Recogn
Example 7 : Creating a Cloud Based People Counter Using MATLAB (ThingSpeak)
Registration of New Face in Webcam through Image Acquisition Toolbox
Label of New Face captured by Webcam
Extract Features for Machine Learning
Machine Learning and Prediction
Performs Real-Time Facial Recognition
Product Focus :
Image Acquisition Toolbox
Image Processing Toolbox
Computer Vision System Toolbox
Machine Learning and Statistic Toolbox
Written at 1 October 2018
Kevin Chng (2023). Real-Time Facial Recognition Using HOG Features (https://github.com/KevinChngJY/real_time_facial_recognition/releases/tag/1.1), GitHub. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
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See release notes for this release on GitHub: https://github.com/KevinChngJY/real_time_facial_recognition/releases/tag/1.1
Modify some error in coding