Social Distancing Detection with Deep Learning Model
Inspection equipment; Learning systems; Object detection; Object recognition; Coronaviruses; Detection tools; Learning models; Model-based OPC; Multiple people; Pedestrian detection; Real-time application; Safe distance; Deep learning
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-252992023-05-29T16:07:59Z Social Distancing Detection with Deep Learning Model Hou Y.C. Baharuddin M.Z. Yussof S. Dzulkifly S. 37067465000 35329255600 16023225600 55569716800 Inspection equipment; Learning systems; Object detection; Object recognition; Coronaviruses; Detection tools; Learning models; Model-based OPC; Multiple people; Pedestrian detection; Real-time application; Safe distance; Deep learning The paper presents a methodology for social distancing detection using deep learning to evaluate the distance between people to mitigate the impact of this coronavirus pandemic. The detection tool was developed to alert people to maintain a safe distance with each other by evaluating a video feed. The video frame from the camera was used as input, and the open-source object detection pre-trained model based on the YOLOv3 algorithm was employed for pedestrian detection. Later, the video frame was transformed into top-down view for distance measurement from the 2D plane. The distance between people can be estimated and any noncompliant pair of people in the display will be indicated with a red frame and red line. The proposed method was validated on a pre-recorded video of pedestrians walking on the street. The result shows that the proposed method is able to determine the social distancing measures between multiple people in the video. The developed technique can be further developed as a detection tool in realtime application. � 2020 IEEE. Final 2023-05-29T08:07:59Z 2023-05-29T08:07:59Z 2020 Conference Paper 10.1109/ICIMU49871.2020.9243478 2-s2.0-85097654416 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097654416&doi=10.1109%2fICIMU49871.2020.9243478&partnerID=40&md5=4a1d359082d077fa51880b6e7768ac1c https://irepository.uniten.edu.my/handle/123456789/25299 9243478 334 338 All Open Access, Bronze Institute of Electrical and Electronics Engineers Inc. Scopus |
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Inspection equipment; Learning systems; Object detection; Object recognition; Coronaviruses; Detection tools; Learning models; Model-based OPC; Multiple people; Pedestrian detection; Real-time application; Safe distance; Deep learning |
| author2 |
37067465000 |
| author_facet |
37067465000 Hou Y.C. Baharuddin M.Z. Yussof S. Dzulkifly S. |
| format |
Conference Paper |
| author |
Hou Y.C. Baharuddin M.Z. Yussof S. Dzulkifly S. |
| spellingShingle |
Hou Y.C. Baharuddin M.Z. Yussof S. Dzulkifly S. Social Distancing Detection with Deep Learning Model |
| author_sort |
Hou Y.C. |
| title |
Social Distancing Detection with Deep Learning Model |
| title_short |
Social Distancing Detection with Deep Learning Model |
| title_full |
Social Distancing Detection with Deep Learning Model |
| title_fullStr |
Social Distancing Detection with Deep Learning Model |
| title_full_unstemmed |
Social Distancing Detection with Deep Learning Model |
| title_sort |
social distancing detection with deep learning model |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806427677499850752 |
| score |
13.222552 |