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Integrate tool for online analysis and offline mining of people trajectories

机译:集成工具,用于人员轨迹的在线分析和离线挖掘

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摘要

In the past literature, online alarm-based video-surveillance and offline forensic-based data mining systems are often treated separately, even from different scientific communities. However, the founding techniques are almost the same and, despite some examples in commercial systems, the cases on which an integrated approach is followed are limited. For this reason, this study describes an integrated tool capable of putting together these two subsystems in an effective way. Despite its generality, the proposal is here reported in the case of people trajectory analysis, both in real time and offline. Trajectories are modelled based on either their spatial location or their shape, and proper similarity measures are proposed. Special solutions to meet real-time requirements in both cases are also presented and the trade-off between efficiency and efficacy is analysed by comparing when using a statistical model and when not. Examples of results in large datasets acquired in the University campus are reported as preliminary evaluation of the system.
机译:在过去的文献中,基于在线警报的视频监视和基于脱机取证的数据挖掘系统通常被分开对待,即使来自不同的科学界也是如此。但是,创建技术几乎相同,尽管在商业系统中有一些示例,但是遵循集成方法的情况是有限的。因此,本研究描述了一种能够有效地将这两个子系统整合在一起的集成工具。尽管具有普遍性,但在实时和离线人员轨迹分析的情况下,此处都报告了该建议。基于轨迹的空间位置或形状对轨迹进行建模,并提出适当的相似性度量。还介绍了在两种情况下均满足实时要求的特殊解决方案,并通过比较使用统计模型和不使用统计模型时的效率和效率之间的取舍进行了分析。报告了在大学校园中获取的大型数据集的结果示例,作为对系统的初步评估。

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  • 来源
    《Computer Vision, IET》 |2012年第4期|p.334-347|共14页
  • 作者单位

    Dipartimento di Ingegneria dell??Informazione, University of Modena and Reggio Emilia, Modena, Italy;

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  • 正文语种 eng
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