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Analytics Based on Video Object Tracking for Surveillance

机译:基于监视视频对象跟踪的分析

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An abandoned object in public places is one of the typical surveillance breaches. Detecting an abandoned object in surveillance video is very important to forecast terrorist activity. This work aims to develop a modular system with several individual stages where in at each stage different algorithm is employed. The overall task is to detect abandoned object in a video stream. This has been implemented in Math Work's MATLAB integrated development environment. The performance of the system is evaluated on test videos from standard publically available datasets and also custom dataset. The Abandoned Object Detection system is tested for two different datasets-publically available i-LiDS AVSS and custom dataset. The metric called system performance used to evaluate our system provided 85.71% result for AVSS dataset and 75% for custom dataset, with overall system performance reaching up to 78.125%.
机译:公共场所的一个被遗弃的物体是典型的监视漏洞之一。在监控视频中检测被遗弃的物体对预测恐怖主义活动非常重要。这项工作旨在开发一个模块化系统,其中包括几个单独的阶段,在每个阶段采用不同的算法。整体任务是在视频流中检测被放弃的对象。这已在数学工作的Matlab集成开发环境中实施。从标准公开可用数据集和自定义数据集的测试视频中评估系统的性能。已被废弃的对象检测系统测试两个不同的数据集 - 公开可用的I-LIDS AVSS和自定义数据集。用于评估我们系统的系统性能的度量标准为AVSS数据集提供了85.71%的结果,以及定制数据集的75%,整体系统性能达到高达78.125%。

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