论文标题
荷胺:基于距离的人类安全风险估计
Inter-Homines: Distance-Based Risk Estimation for Human Safety
论文作者
论文摘要
在本文档中,我们报告了我们在RGB摄像机监控的给定区域中建模可能具有传染性风险的建议。我们的系统称为互惠剂,通过分析视频流来实时评估受监视区域中的传染风险:它能够在3D空间中找到人们,计算人际距离并通过构建受监视区域的动态图来预测风险水平。互联网在公共和私人拥挤的地区都在室内和室外工作。该软件适用于已安装的相机或工业PC上的低成本摄像头,配备了额外的嵌入式边缘AAI系统,用于临时测量。从AI侧来看,我们通过基于最先进的计算机视觉算法的同源转换来利用强大的管道将实时人员检测和在接地平面中进行定位;它是人探测器和姿势估计器的组合。从风险建模方面,我们提出了一个用于时空动态风险估计的参数模型,该模型通过流行病学家验证,可以通过预测现场风险水平来安全监视对社会距离预防措施的接受。
In this document, we report our proposal for modeling the risk of possible contagiousity in a given area monitored by RGB cameras where people freely move and interact. Our system, called Inter-Homines, evaluates in real-time the contagion risk in a monitored area by analyzing video streams: it is able to locate people in 3D space, calculate interpersonal distances and predict risk levels by building dynamic maps of the monitored area. Inter-Homines works both indoor and outdoor, in public and private crowded areas. The software is applicable to already installed cameras or low-cost cameras on industrial PCs, equipped with an additional embedded edge-AI system for temporary measurements. From the AI-side, we exploit a robust pipeline for real-time people detection and localization in the ground plane by homographic transformation based on state-of-the-art computer vision algorithms; it is a combination of a people detector and a pose estimator. From the risk modeling side, we propose a parametric model for a spatio-temporal dynamic risk estimation, that, validated by epidemiologists, could be useful for safety monitoring the acceptance of social distancing prevention measures by predicting the risk level of the scene.