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Forensic reasoning upon pre-obtained surveillance metadata using uncertain spatio-temporal rules and subjective logic

机译:使用不确定的时空规则和主观逻辑对预先获取的监视元数据进行法医推理

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The majority of recent work in forensic analysis of visual surveillance content has been focusing on automatic information extraction aspects. However, little attention has been paid to the intelligent reuse of extracted (meta)data. For reasoning upon such pre-acquired metadata, in our previous paper [1], we proposed the use of logic programming to represent human knowledge and the use of subjective logic [2] to handle uncertainty implied in the extracted data and the logical rules. In this paper, we further explore the proposed approach for analyzing the relationship between two persons and, more specifically, for estimating whether one person could serve as a witness of another person in a public area scene. We first develop a rule based model for the likelihood of being a good witness that uses metadata extracted by a person tracker and evaluates the relationship between the tracked persons. To cope with the uncertainty in the relationship model, we develop a reputational subjective opinion function for the spatial-temporal relations. In addition, we accumulate the acquired opinions over time using subjective logic's fusion operator. To verify our approach, we finally present a preliminary experimental case study.
机译:视觉监视内容的法医分析方面的最新工作主要集中在自动信息提取方面。但是,很少有人关注提取的(元)数据的智能重用。为了对这样的预先获取的元数据进行推理,在我们以前的论文[1]中,我们提出了使用逻辑编程来表示人类知识,并提出了使用主观逻辑[2]来处理所提取的数据和逻辑规则中隐含的不确定性。在本文中,我们将进一步探索建议的方法,以分析两个人之间的关系,更具体地说,是估计一个人是否可以在公共场所场景中充当另一个人的证人。我们首先开发一个基于规则的模型,以便成为好证人的可能性,该模型使用人员跟踪器提取的元数据并评估被跟踪人员之间的关系。为了应对关系模型中的不确定性,我们针对时空关系开发了声誉主观意见函数。此外,我们使用主观逻辑的融合算子随时间累积获得的意见。为了验证我们的方法,我们最终提出了一个初步的实验案例研究。

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