论文标题
伦敦接近实时的社交距离估计
Near Real-Time Social Distance Estimation in London
论文作者
论文摘要
在Covid-19大流行期间，大伦敦当局的政策制定者，英国伦敦的地区治理机构，依赖于迅速而准确的数据源。有时很难获得整个城市中大量明确定义的非均质活动组成，但是为了学习“忙碌”并因此做出安全的政策决定是必要的。在这个领域，我们项目的一个组成部分是利用现有的基础设施来估计公众的社会距离依从性。我们的方法可以通过现场交通摄像头饲料即可立即采样和伦敦街道上的活动和物理距离的上下文化。我们引入了一个框架，以检查和改进现有方法，同时还描述了其在900多个实时供稿上的主动部署。
During the COVID-19 pandemic, policy makers at the Greater London Authority, the regional governance body of London, UK, are reliant upon prompt and accurate data sources. Large well-defined heterogeneous compositions of activity throughout the city are sometimes difficult to acquire, yet are a necessity in order to learn 'busyness' and consequently make safe policy decisions. One component of our project within this space is to utilise existing infrastructure to estimate social distancing adherence by the general public. Our method enables near immediate sampling and contextualisation of activity and physical distancing on the streets of London via live traffic camera feeds. We introduce a framework for inspecting and improving upon existing methods, whilst also describing its active deployment on over 900 real-time feeds.
