OVERVIEW of Face Recognition based Door Lock using Raspberry Pi B+ OpenCV
Face recognition is an amazing field of computer vision with many possible applications to hardware and devices. Using embedded SOC platforms like the Raspberry Pi and open source computer vision libraries like OpenCV, you can now add face recognition to your own maker projects! In this project, I’ll show you how to build a face recognition based door lock which unlocks itself using face recognition running on a Raspberry Pi.
For this face recognition based door lock project, you need basic skills related to Linux, Raspberry Pi and electronics. If you are not confident with Raspberry Pi you can take any free tutorial from YouTube.
If you are looking for other IOT projects please check this link >>>>
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- Raspberry Pi 3 B+
- SD Card 16GB 98Mbps For Fast Performance
- Raspberry Pi Camera
- Servo Motor
- 10k -ohm 1/4 watt resistor
- Push Button
- Hookup Wires
- 6V Power Supply for Servo
- Wood / Glue and Misc for Construction
PROJECT GUIDE AND TUTORIAL
My Door Lock is based on this below adafruit Tutorial by Toiy DiCola
Please follow his tutorial to learn how this is made. Below is a video of my project’s demonstration.
This implementation of facial recognition involves Principal component analysis (PCA) and Eigenfaces. The Principal Component Analysis (PCA) was independently proposed by Karl Pearson (1901) and Harold Hotelling (1933) to turn a set of possibly correlated variables into a smaller set of uncorrelated variables. The idea is, that a high-dimensional dataset is often described by correlated variables and therefore only a few meaningful dimensions account for most of the information. The PCA method finds the directions with the greatest variance in the data, called principal components.
Here is the documentation for Eigenface and its implementation >>>
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Credits: Adafruit, Tony DiCola