International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 184 - Number 28 |
Year of Publication: 2022 |
Authors: Object Detection To Monitor COVID-19 Safety Measures, Mohd Moiz Uddin Zeeshan, Mohd Shadab, Mohammed Sheeraz Mehdi |
10.5120/ijca2022922349 |
Object Detection To Monitor COVID-19 Safety Measures, Mohd Moiz Uddin Zeeshan, Mohd Shadab, Mohammed Sheeraz Mehdi . Object Detection To Monitor COVID-19 Safety Measures. International Journal of Computer Applications. 184, 28 ( Sep 2022), 18-21. DOI=10.5120/ijca2022922349
This research utilizes object detection and machine learning to simultaneously detect face masks and social distance in video feeds. Tensor flow and Keras were used to create a CNN model for identifying face masks. A dataset of about 4000 photos was used to train this model. By marking the centroid and calculating the Euclidean distance between them using the k-means algorithm, an object detection model was utilized to concurrently recognize people in a rectangle frame and check for social distance between two people using their face masks. The backend service was Firebase. If the permissible number of violations is surpassed, the image will be uploaded to Firebase's cloud storage and a warning email will be forwarded to the relevant authorities.