Publication:
Social Distancing Detection with Deep Learning Model

Simple item page
dc.citedby50
dc.contributor.authorHou Y.C.en_US
dc.contributor.authorBaharuddin M.Z.en_US
dc.contributor.authorYussof S.en_US
dc.contributor.authorDzulkifly S.en_US
dc.contributor.authorid37067465000en_US
dc.contributor.authorid35329255600en_US
dc.contributor.authorid16023225600en_US
dc.contributor.authorid55569716800en_US
dc.date.accessioned2023-05-29T08:07:59Z
dc.date.available2023-05-29T08:07:59Z
dc.date.issued2020
dc.descriptionInspection 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 learningen_US
dc.description.abstractThe 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9243478
dc.identifier.doi10.1109/ICIMU49871.2020.9243478
dc.identifier.epage338
dc.identifier.scopus2-s2.0-85097654416
dc.identifier.spage334
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097654416&doi=10.1109%2fICIMU49871.2020.9243478&partnerID=40&md5=4a1d359082d077fa51880b6e7768ac1c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25299
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitle2020 8th International Conference on Information Technology and Multimedia, ICIMU 2020
dc.titleSocial Distancing Detection with Deep Learning Modelen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
Files
Collections
SCOPUS