Real Time Face Mask and Social Distancing Detection System Using Deep Learning |
Author(s): |
| Bhagyashri Chhaganlal Borikar , Nagpur Institute of Technology, Nagpur.; Prof. Mahvash Iram Khan , Nagpur Institute of Technology, Nagpur.; Ms. Garima Rai, Nagpur Institute of Technology, Nagpur.; Ms. Anjali Kharapkar, Nagpur Institute of Technology, Nagpur.; Ms. Chetana Likhar, Nagpur Institute of Technology, Nagpur. |
Keywords: |
| Convolution neural networks, OpenCV, TensorFlow, YOLO v3 algorithm, Face Mask Detection, Social distancing, Deep learning, Human detection, Video processing |
Abstract |
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The rapid spread of Covid-19 is become a pandemic and has created abrupt changes in society. Outdoor work in industries, institutes, etc. is stuck up. The presented work consists of two parts. In the first part, the dataset is pre-process and labelled as faces with face mask and without face mask using deep learning solution that uses OpenCV and TensorFlow to train the model i.e. Convolution neural network is used. In the second part, the human body is detected and safe distance i.e. 2m, between two bounding boxes of human bodies is calculated and image data is created. This created image data is now matched with the existing image dataset. For this purpose, the YOLO v3 algorithm is used. |
Other Details |
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Paper ID: IJSRDV9I40038 Published in: Volume : 9, Issue : 4 Publication Date: 01/07/2021 Page(s): 676-680 |
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