Exploring Internet of Thing on PCA Algorithm for Optimization of Facial Detection and Tracking

Abstract

This work was able to integrate Internet of Things expertise on Principal Count Analysis (PCA) algorithm for facial recognition optimization. An internet-based real-time facial recognition system was developed using PCA algorithm that can detect and track faces, a label name that indicates the face identified was also incorporated to easily track the face in situations where multiple faces are identified at the same time. A router was used to set up a wireless connection with an internet protocol (IP)-camera via the IP-camera firmware. As the router broadcast this connection, a link is set up with a personal computer through the network and sharing centre tab on the computer system, thereby creating a wireless connection between the computer and the camera on the internet. Graphical interface designed on MATLAB was used to access the feed from the camera which PCA algorithm explored in detecting and tracking faces in real-time. Security features such as timestamp and database were also integrated with the system developed.