Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia.
Sensors (Basel). 2013 Aug 5;13(8):9966-98. doi: 10.3390/s130809966.
Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition.
事件识别是视频监控领域中最活跃的研究领域之一。事件识别系统的发展主要旨在为人类提供便利、安全和高效的生活方式。为了使事件识别系统能够应对各种不可控环境(如紧急情况、身体威胁、火灾或炸弹警报)中的突发变化,需要一种精确、准确和稳健的方法。突发事件识别系统的性能在很大程度上取决于低级处理(如检测、识别、跟踪和机器学习算法)的准确性。本调查旨在检测和描述突发事件,这是几个视频监控应用中异常事件的一个子集。本文详细讨论了以下内容:(1)突发事件相对于一般异常事件的重要性;(2)突发事件识别中使用的框架;(3)突发事件识别系统的要求和比较研究;(4)突发事件识别的各种决策方法。还讨论了使用来自多个摄像机的 3D 图像进行实时应用的优缺点。本文最后提出了突发事件识别的未来研究方向的建议。