Rapid Face Mask Detection and Person Identification Model based on Deep Neural Networks

TL;DR

This paper introduces RFMPI-DNN, a deep neural network model that rapidly detects face masks and identifies persons, outperforming previous models in speed and accuracy, aiding COVID-19 prevention efforts.

Contribution

The paper presents a novel deep learning model combining SoftMax and Arc Face loss for fast face mask detection and person recognition, improving on existing models.

Findings

RFMPI-DNN outperforms MobileNet_V2 in detection speed.

The model achieves higher accuracy in face mask and person identification.

System implementation demonstrates improved real-time performance.

Abstract

As Covid-19 has been constantly getting mutated and in three or four months a new variant gets introduced to us and it comes with more deadly problems. The things that prevent us from getting Covid is getting vaccinated and wearing a face mask. In this paper, we have implemented a new Face Mask Detection and Person Recognition model named Insight face which is based on SoftMax loss classification algorithm Arc Face loss and names it as RFMPI-DNN(Rapid Face Detection and Peron Identification Model based on Deep Neural Networks) to detect face mask and person identity rapidly as compared to other models available. To compare our new model, we have used previous MobileNet_V2 model and face recognition module for effective comparison on the basis of time. The proposed model implemented in the system has outperformed the model compared in this paper in every aspect