Abstract: After the breakout of the worldwide pandemic COVID-19, there arises a severe need of protection mechanisms, face mask being the primary one. The basic aim of the project is to detect the presence of a face mask on human faces on live streaming video as well as on images. We have used deep learning to develop our face detector model. The architecture used for the object detection purpose is Single Shot Detector (SSD) because of its good performance accuracy and high speed. Alongside this, we have used basic concepts of transfer learning in neural networks to finally output presence or absence of a face mask in an image or a video stream. Experimental results show that our model performs well on the test data with 100% and 99% precision and recall, respectively. Identifying a person by face is quite a trend nowadays. but here we are going to check whether the person is wearing mask or not. And then we can detect whether the person is an authorized person or an unauthorized person. We are going to use the Open-CV and CNN (Convolution Neural Network) to detect the presence of mask and to detect the person's identity. For face detection, Haar-cascade is used, for face recognition Eigen faces and fisher faces are used. When we find an unauthorized person. The system can be able to generate an alert e-mail and send it to the concerned e-mail address. And the graphs are drawn using Matplotlib library.
Keywords: covid, facemask, deeplearning, detection, email, warning
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DOI:
10.17148/IJARCCE.2022.116110
