Efficiency and accuracy: comparison of PIR, OpenCV with a webcam, and Raspberry Pi

This paper is dedicated to developing and evaluating the facial recognition system, focusing on its effectiveness and operational reliability under real-world conditions. The choice of the Raspberry Pi hardware platform for implementing the system has been justified by its capability to process video streams in real time, as well as its compatibility with the high-quality Raspberry Pi Camera V2, which enables the acquisition of images with sufficient resolution for the proper functioning of computer vision algorithms. The implementation of a prototype of the studied system has been presented, encompassing the development of a face detection algorithm, hardware configuration, integration of the OpenCV, Dlib, and Picamera2 libraries, as well as the use of pre-trained models for accurate detection of facial key points. The developed algorithm has been adapted and optimized to consider the limited hardware resources of the Raspberry Pi platform, ensuring high accuracy and real-time image processing performance.