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Sensors 2013, 13(8), 9966-9998; doi:10.3390/s130809966

Sudden Event Recognition: A Survey

Smart Engineering System Research Group, Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
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Received: 30 June 2013 / Revised: 26 July 2013 / Accepted: 26 July 2013 / Published: 5 August 2013
(This article belongs to the Section Physical Sensors)
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Abstract

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.
Keywords: sudden event recognition; motion pattern; video surveillance; foreground detection; object tracking; object recognition sudden event recognition; motion pattern; video surveillance; foreground detection; object tracking; object recognition
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Suriani, N.S.; Hussain, A.; Zulkifley, M.A. Sudden Event Recognition: A Survey. Sensors 2013, 13, 9966-9998.

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