Towards Fast and Accurate Intimate Contact Recognition through Video Analysis
11th International Conference on Image Processing Theory, Tools and Applications, IPTA 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-1922716
ABSTRACT
Intimate contact recognition has gained more attention in academia field in recent years due to the outbreak of Covid-19. However, state of the art solutions suffer from either inefficient accuracy or high cost. In this paper, we propose a novel method for COVID-19 intimate contact recognition in public spaces through video camera networks (CCTV). This method leverages distance detection and re-Identification algorithms, so pedestrians in close contact are re-identified, their identity information is obtained and stored in a database to realize contact tracing. We compare different social distance detection algorithms and the Faster-RCNN model outperforms other al-ternatives in terms of running speed. We also evaluate our Re-Identification model on two types of indicators in the PETS2009 dataset mAP reaches 85.1%;rank-1, rank-5, and rank-10 reach 97.8%, 98.9%, and 98.9%, respectively. Experimental results demonstrate that our solution can be effectively applied in public places to realize fast and accurate automatic contact tracing. © 2022 IEEE.
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
11th International Conference on Image Processing Theory, Tools and Applications, IPTA 2022
Year:
2022
Document Type:
Article
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