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http://dx.doi.org/10.3745/KTSDE.2021.10.7.279

A Study on the Estimation of Multi-Object Social Distancing Using Stereo Vision and AlphaPose  

Lee, Ju-Min (성균관대학교 인공지능융합학부)
Bae, Hyeon-Jae (차세대융합기술연구원 컴퓨터비전 및 인공지능 연구실)
Jang, Gyu-Jin (차세대융합기술연구원 컴퓨터비전 및 인공지능 연구실)
Kim, Jin-Pyeong (차세대융합기술연구원 컴퓨터비전 및 인공지능 연구실)
Publication Information
KIPS Transactions on Software and Data Engineering / v.10, no.7, 2021 , pp. 279-286 More about this Journal
Abstract
Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.
Keywords
Stereo Vision; Distacne Estimation; Object Detection; Skeleton Extraction; Multi-Object;
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