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视频监控的周界入侵检测:综述。

Perimeter Intrusion Detection by Video Surveillance: A Survey.

机构信息

Univ Lyon, Univ Lyon 2, CNRS, INSA Lyon, UCBL, LIRIS, UMR5205, F-69676 Bron, France.

Foxstream, F-69120 Vaulx-en-Velin, France.

出版信息

Sensors (Basel). 2022 May 9;22(9):3601. doi: 10.3390/s22093601.

Abstract

In recent times, we have seen a massive rise in vision-based applications, such as video anomaly detection, motion detection, object tracking, people counting, etc. Most of these tasks are well defined, with a clear idea of the goal, along with proper datasets and evaluation procedures. However, perimeter intrusion detection (PID), which is one of the major tasks in visual surveillance, still needs to be formally defined. A perimeter intrusion detection system (PIDS) aims to detect the presence of an unauthorized object in a protected outdoor site during a certain time. Existing works vaguely define a PIDS, and this has a direct impact on the evaluation of methods. In this paper, we mathematically define it. We review the existing methods, datasets and evaluation protocols based on this definition. Furthermore, we provide a suitable evaluation protocol for real-life application. Finally, we evaluate the existing systems on available datasets using different evaluation schemes and metrics.

摘要

近年来,基于视觉的应用程序如视频异常检测、运动检测、目标跟踪、人数统计等得到了广泛的应用。这些任务大多定义明确,目标清晰,同时还有适当的数据集和评估程序。然而,作为视觉监控的主要任务之一的周界入侵检测(PID)仍然需要正式定义。周界入侵检测系统(PIDS)旨在检测在特定时间段内受保护的室外场地是否存在未经授权的物体。现有的工作只是模糊地定义了 PIDS,这直接影响了方法的评估。在本文中,我们对其进行了数学定义。我们基于这个定义来回顾现有的方法、数据集和评估协议。此外,我们还提供了一个适合实际应用的评估协议。最后,我们使用不同的评估方案和指标在现有的数据集上评估现有的系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62d9/9104546/cf17c66e1d3b/sensors-22-03601-g0A1.jpg

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