Autors: Neshov, N. N., Manolova, A. H., Tonchev K., Poulkov, V. K.
Title: Real-time estimation of distance between people and/or objects in video surveillance
Keywords: Cameras , Estimation , Diseases , Social factors , Human factors , Real-time systems , Calibration

Abstract: Social distancing is not just about keeping away from loved ones, shutting schools or working from home. A strict physical separation must be maintained in order to prevent the spread of COVID-19. Yet, front-line workers in healthcare, public safety, retail, manufacturing and transportation and logistics have found it particularly challenging to maintain the 1,5 to 2 meters separation from other people while doing their everyday jobs. In this paper we have presented a simple real-time method for distance estimation with any kind of camera between people applicable either in close quarters or open spaces. The aim is to help easily and non obtrusively alert if the correct distance between people is not maintained. The initial results are promising and the error between the real and the measured values is in statistical margin. At the same time, the proposed system monitors people without facial recognition. The data collected is anonymous and do not require the use of facial recognition

References

    Issue

    23rd International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 1-4, 2020, Japan, IEEE, DOI 10.1109/WPMC50192.2020.9309512

    Copyright IEEE

    Цитирания (Citation/s):
    1. Lee, J. M., Bae, H. J., Jang, G. J., & Kim, J. P. (2021). A Study on the Estimation of Multi-Object Social Distancing Using Stereo Vision and AlphaPose. KIPS Transactions on Software and Data Engineering, 10(7), 279-286. - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus