智能视频监控中的异常活动检测技术综述

S.Sony Priya, R. Minu
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引用次数: 0

摘要

目前,CCTV(闭路电视)摄像机用于监控,如果发生任何故障或异常活动,它会提醒保安人员。异常活动可能是偷窃、暴力或爆炸。闭路电视摄像机被用于城市街道、公园、社区和邻里等公共场所,以帮助侦查犯罪和加强公共安全。为此进行手动监视既乏味又耗时。实时检测人群异常行为是一个令人兴奋的研究领域。目前,大多数研究人员都对开发动态异常检测机制来保证安全感兴趣。然而,由于气候变化、人类运动、遮挡和低视频质量,这是具有挑战性的。由于视频数据的高维性,也增加了空间和时间复杂度。本文介绍了深度学习和手工方法下异常活动检测的各种方法。
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Abnormal Activity Detection Techniques in Intelligent Video Surveillance: A Survey
Currently, CCTV (Closed Circuit Television) cameras are used for surveillance by alerting the security officer if any malfunction or abnormal activity happens. Abnormal activities may be theft, violence, or explosion. CCTV cameras are used in public places like city streets, parks, communities, and neighborhoods to help detect crime and enhance public safety. Manual surveillance for this is tedious and time-consuming. Detecting abnormal crowd behavior in real-time is an exciting research area. Presently, most researchers are interested in developing Dynamic abnormal detection mechanisms to ensure security. However, this is challenging due to climate change, human movement, occlusions, and low video quality. Due to the high dimensionality of video data, Space and time complexity are also increased. This paper explains the various methods of abnormal activity detection under deep learning and the handcrafted approach.
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