流行病期间户外社交距离行为发生了变化:使用街景图像进行纵向分析
Matthew Martell1, Chris Salazar1, Nicole A Errett2
1Industrial & Systems Engineering, University of Washington, Seattle, WA, United States of America.
PloS one
|December 5, 2024
概括
这项研究分析了COVID-19期间使用街景图像的行人社交距离. 遵守身体距离指导方针因疫苗的可用性,季节和地点而有所不同.
科学领域:
- 流行病学 流行病学
- 计算机视觉 计算机视觉
- 城市研究 城市研究
背景情况:
- 社交距离是控制传染病的关键非药物干预措施.
- 之前的研究经常使用手机数据;对人际距离的遵守缺乏大规模分析.
研究的目的:
- 用计算机视觉量化分析户外社交距离行为.
- 调查影响遵守人际距离准则的因素.
主要方法:
- 在COVID-19大流行期间利用了来自西雅图的三年街景图像.
- 采用计算机视觉来检测行人,以及基于几何的算法来计算行人之间的距离.
主要成果:
- 社会距离行为与疫苗可用性,季节性和当地社会经济数据相关.
- 在不同兴趣点 (公园,学校等) 中发现了隔离行为的变化. ) 的情况.
结论:
- 这项研究使用计算机视觉对户外社交距离进行了新的纵向分析.
- 调查结果为决策者提供了洞察力,以管理在城市户外环境中传染病传播风险.
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