关键视频监控与人的行为识别ATM安全系统分析

M. Sivabalakrishnan, R. Menaka, S. Jeeva
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引用次数: 1

摘要

视频监控摄像机被放置在银行、医院、收费站、机场等许多地方。为了实时利用视频,必须有人持续监控系统,以便在发生紧急情况时向保安人员发出警报。此外,对于事件检测,一个人可以同时观察四个摄像机,并且精度很高。因此,使用现有技术进行实时视频监控需要昂贵的人力资源。在记录以上空间和时间的同时,获得一个或多个目标的轨迹,用于目标跟踪。通过对各种目标的跟踪,大大减轻了哨兵的检测负担。高效可靠的自动报警系统是许多ATM监控应用的重要组成部分。ATM视频监控系统在人类异常行为检测方法方面提出了许多具有挑战性的研究问题。本章简要讨论了ATM视频监控系统的框架,包括图像采集、背景估计、背景减除、分割、人员计数和跟踪等各个方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Critical Video Surveillance and Identification of Human Behavior Analysis of ATM Security Systems
Video surveillance cameras are placed in many places such as bank, hospital, toll gates, airports, etc. To take advantage of the video in real time, a human must monitor the system continuously in order to alert security officers if there is an emergency. Besides, for event detection a person can observe four cameras with good accuracy at a time. Therefore, this requires expensive human resources for real time video surveillance using current technology. The trajectory of one or more targets obtains for object tracking while recording above space and time. By tracking various objects, the burden of detection by human sentinels is greatly alleviated. Efficient and reliable automatic alarm system is useful for many ATM surveillance applications. ATM Video monitoring systems present many challenging research issues in human abnormal behaviors detection approaches. The framework of ATM video surveillance system encompassing various factors, such as image acquisition, background estimation, background subtraction, segmentation, people counting and tracking are briefly discussed in this chapter.
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