监视应用中的异常事件检测方法

T. J. N. Rao, G. Girish, M. Tahiliani, Jeny Rajan
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引用次数: 0

摘要

自动视觉监视系统作为即时威胁侦测装置,能够侦测和识别可能导致潜在有害情况的异常活动,并提醒有关当局采取适当的对抗行动。然而,开发一种高效的视觉监控系统是相当具有挑战性的。设计一种准确、实时的异常活动检测机制是主要的挑战。通过对文献的回顾,我们得出结论,对于一个成功的异常事件检测机制来说,有一些属性是必不可少的。理想的方法必须以可接受的精度检测现实场景中的真正异常,应该适应不断变化的环境,并且应该需要更少的计算时间和内存。在本章中,试图提供一些研究人员用来解决这些问题的突出方法的见解,希望它将有利于研究人员开发更好的监测系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anomalous Event Detection Methodologies for Surveillance Application
Automatic visual surveillance systems serve as in-place threat detection devices being able to detect and recognize anomalous activities which otherwise would lead to potentially harmful situations, and alert the concerned authorities to take appropriate counter actions. However, development of an efficient visual surveillance system is quite challenging. Designing an unusual activity detection mechanism which is accurate and real-time is the primary challenge. Review of literature carried out led to the inference that there are some attributes which are essential for a successful unusual event detection mechanism for surveillance application. The desired approach must detect genuine anomalies in real-world scenarios with acceptable accuracy, should adapt to changing environments and, should require less computational time and memory. In this chapter, an attempt has been made to provide an insight into some of the prominent approaches employed by researchers to solve these issues with a hope that it will benefit researchers towards developing a better surveillance system.
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