A Computer Vision Framework for Human User Sensing in Public Open Spaces
A Computer Vision Framework for Human User Sensing in Public Open Spaces
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DOI：
10.1145/3360773.3360880
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发表时间：
2019-11
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影响因子：
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通讯作者：
Peng Sun;R. Hou;J. Lynch
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文献类型：
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作者：
Peng Sun;R. Hou;J. Lynch
城市设计领域考虑人们在设计公园、广场和街道等空间时如何利用公共开放空间 (POS)。目前观察公共空间使用情况的方法依赖于目视观察，这需要花费大量的时间和精力来检测大型POS中用户的身体活动；这些方法也仅提供对顾客在这些区域的行为方式的定性观察。有源传感器，例如可穿戴传感器和具有GPS跟踪功能的智能手机，成本较高，并且无法感知POS中的所有用户（即，此类传感器对没有可穿戴传感器的用户“视而不见”）。因此，利用 POS 中预装监控摄像头的视频数据，利用计算机视觉方法从视频中提取 POS 使用信息是很有吸引力的。本文提出了一种基于计算机视觉的传感框架来测量 POS 中的人类活动。作为研究的一部分，使用广泛标记的人员及其在 POS 中的活动（称为 OPOS）的数据集来训练检测器。使用底特律河滨绿道的安全摄像头反馈，对所提出的框架进行了案例研究。经过训练的检测器的 AP0.50 结果对于行人检测和骑车人检测分别为 96.3% 和 96.5%。这些结果表明，这种方法可以可靠地跟踪公园内的顾客，以确定他们的行为并为未来的 POS 改进提供信息。
The field of Urban design considers how people utilize public open spaces (POS) when designing spaces such as parks, plazas, and streets. Current methods of observing public space use rely on visual observation which consumes much time and effort to detect users' physical activities in large POS; these methods also only provide qualitative observations of how patrons behave in these areas. Active sensors, such as wearable sensors and smart phones with GPS tracking capabilities, have high costs and cannot sense all users in a POS (namely, such sensors are "blind to" those without wearable sensors). Therefore, it is appealing to make use of video data from pre-installed surveillance cameras in POS to extract POS use information from video using computer vision methods. This paper proposes a sensing framework based on computer vision to measure human activities in POS. As part of the study, an extensively labeled datset of people and their activities in POS (termed OPOS) is used to train detectors. A case study of the proposed framework is presented using security camera feeds from a greenway at the Detroit Riverfront. The AP0.50 results of the trained detector are 96.3% for pedestrian detection and 96.5% for cyclist detection, respectively. These results show such an approach can reliably track patrons in parks to ascertain their behavior and to inform future POS improvements.