Physical distance monitoring system for COVID-19 using raspberry Pi and a monocular camera: poster abstract

ABSTRACT

During the global pandemic of coronavirus disease 2019 (COVID-19), it is crucial to minimize the spread of the infection until effective drugs and vaccines are developed. Therefore, close contact must be reduced to prevent human-to-human transmission. We propose a simplified inexpensive system using a monocular camera combined with Raspberry Pi, a small single-board computer, to measure physical distancing and warn people of their proximity with others.

References

1. World Health Organization. Global surveillance for covid-19 caused by human infection with covid-19 virus, 2020.
2. Dongfang Yang et al. A vision-based social distancing and critical density detection system for covid-19, 2020.
3. Sven Kreiss et al. Pifpaf: Composite fields for human pose estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 11977--11986, June 2019.
4. Lorenzo Bertoni et al. Monoloco: Monocular 3d pedestrian localization and uncertainty estimation. pages 6860--6870, 10 2019.
5. Xiangyu Zhang et al. Shufflenet: An extremely efficient convolutional neural network for mobile devices. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 6848--6856, June 2018.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Computer vision problems

        • Tracking