People Monitoring and Mask Detection using Real-time video analyzing

EOI: 10.11242/viva-tech.01.04.086

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Mr. Yogesh Gowari, Mr. Ritik Gaikwad, Mr. Aniket Gurav, Prof. Vinit Raut, "People Monitoring and Mask Detection using Real-time video analyzing", VIVA-IJRI Volume 1, Issue 4, Article 86, pp. 1-4, 2021. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.


People Counting and mask detection based on video is an important field in a Computer Vision. There is growing interest in video-based solutions for people monitoring and counting in business and security applications using Computer Vision technology. It has been effectively used in many Artificial Intelligence fields. Comparing to normal sensor based solutions the one with video based allows more flexible performance, improved functionalities with lower costs. The system with people counter program requires more processing because that deals with real-time video, so this particular proposed technique converts a color image into binary in order to minimize data of image. Reducing processing time is an important term in Software Engineering to build a good working system. People counting methods based on head detection and tracking to evaluate the total number of people who move under an overhead camera and check whether that people wearing a mask or not wearing a mask. There are basically four main features within this proposed system: counting of people, detection of mask, alerting alarm and Scanning of ID. Based on the tracking of the head, this method is using the crossing-line judgment to determine whether a particular head object will be getting counted or not getting counted. The two main challenges which have overcome in this system are: tough estimation of the moving background scene and the number of the people in merge split scenarios. The technique for an masked face detection using three different steps of estimating are eye line detection, facial part detection and eye detection is used in the following system. On being exceeding the count of people or in case mask is seen not worn then alarm gets alerted.


Convolution Neural Network, ComputerVision, Dataset, MobileNet SSD, Mask detection.


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