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A Personnel Detection Algorithm for an Intermodal Maritime Application of ITS Technology for Security at Port Facilities

机译:ITS技术在港口设施联运中海事应用的人员检测算法

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With an overwhelming number of containers entering the United States on a daily basis, ports of entry are causing major concerns for homeland security. The disruption to commerce to inspect all containers would be prohibitive. Currently, fences and port security patrols protect these container storage yards. To improve security system performance, the authors propose a low cost fully distributed Intelligent Transportation System based implementation. Based on prior work accomplished in the design and fielding of a similar system in the United States, current technologies can be assembled, mixed and matched, and scaled to provide a comprehensive security system. We also propose the incorporation of a human detection algorithm to enhance standard security measures. The human detector is based on the histogram of oriented gradients detec- tion approach and the Haar-like feature detection approach. According to the conducted experimental results, merging the two detectors, results in a human detector with a high detection rate and lower false posi- tive rate. This system allows authorized operators on any console to control any device within the facility and monitor restricted areas at any given time.
机译:每天有大量的集装箱进入美国,进入港口正引起国土安全的重大关切。检查所有容器的商业中断将是禁止的。目前,围栏和港口安全巡逻队保护着这些集装箱堆场。为了提高安全系统的性能,作者提出了一种基于低成本,完全分布式的智能交通系统的实施方案。根据在美国类似系统的设计和部署中完成的先前工作,可以对当前技术进行组装,混合和匹配,然后进行缩放以提供全面的安全系统。我们还建议采用人工检测算法,以增强标准的安全措施。人体检测器基于定向梯度直方图检测方法和类似Haar的特征检测方法。根据进行的实验结果,将两个检测器合并在一起,可以使人类检测器具有较高的检测率和较低的假阳性率。该系统允许任何控制台上的授权操作员在任何给定时间控制设施内的任何设备并监视限制区域。

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