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Assessing the Threat of Firearms: New Threat Formula, Resources, and Ontological Linking Algorithms

机译:评估枪支威胁:新的威胁公式,资源和本体链接算法

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摘要

The present work is part of an ongoing larger project. The goal of this project is to develop a system capable of automatic threat assessment for instances of firearms use in public places. The main components of the system are: an ontology of firearms; algorithms to create the visual footprint of the firearms, to compare visual information, to facilitate search in the ontology, and to generate the links between the conceptual and visual ontologies; as well as a formula to calculate the threat of individual firearms, firearms classes, and ammunition types in different environments. One part of the dual-level ontology for the properties of the firearms captures key visual features used to identify their type or class in images, while the other part captures their threat-relevant conceptual properties. The visual ontology is the result of image segmentation and matching methods, while the conceptual ontology is designed using knowledge-engineering principles and populated semi-automatically from Web resources. The focus of the present paper is two-fold. On the one hand, we will report on an update of the initial threat formula, based on the substantially increased population of the firearm ontology, including ammunition types and comparisons to actual incidents, and allowing for an overall more accurate assessment. On the other hand, the linking algorithms between the visual and conceptual ontologies are elaborated for faster transfer of information leading to an improvement in accuracy of the threat assessment.
机译:目前的工作是正在进行的较大项目的一部分。该项目的目标是开发一种能够对公共场所使用的枪支进行自动威胁评估的系统。该系统的主要组成部分是:枪支本体;创建枪支的视觉足迹,比较视觉信息,促进本体搜索以及在概念本体和视觉本体之间建立联系的算法;以及用于计算不同环境中单个枪支,枪支类别和弹药类型的威胁的公式。枪支属性的双层本体的一部分捕获了关键的视觉特征,这些视觉特征用于识别图像中的类型或类别,而另一部分捕获了与威胁相关的概念特性。视觉本体是图像分割和匹配方法的结果,而概念本体是使用知识工程原理设计的,并从Web资源中自动填充。本文的重点是两个方面。一方面,我们将基于枪支本体的大量增加(包括弹药类型和与实际事件的比较),报告初始威胁公式的更新,并允许进行整体更准确的评估。另一方面,精心设计了视觉本体和概念本体之间的链接算法,以加快信息传递速度,从而提高威胁评估的准确性。

著录项

  • 来源
  • 会议地点 Baltimore MD(US)
  • 作者单位

    Ontological Semantic Technology Lab Texas A M University - Commerce, TX 75428, USA,Department of Literature and Languages Texas A M University - Commerce, TX 75428, USA;

    Ontological Semantic Technology Lab Texas A M University - Commerce, TX 75428, USA,Department of Computer Science and Information Systems Texas A M University - Commerce, TX 75428, USA;

    Ontological Semantic Technology Lab Texas A M University - Commerce, TX 75428, USA,College of Humanities, Social Sciences, and Arts Texas A M University - Commerce, TX 75428, USA;

    Ontological Semantic Technology Lab Texas A M University - Commerce, TX 75428, USA,Department of Physics and Astronomy Texas A M University - Commerce, TX 75428, USA;

    Ontological Semantic Technology Lab Texas A M University - Commerce, TX 75428, USA,Department of Computer Science and Information Systems Texas A M University - Commerce, TX 75428, USA,Department of Mathematics Texas A M University - Commerce, TX 75428, USA;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    features extraction; weapon ontology; visual/conceptual hierarchy; convergence; weapon identification; threat assessment;

    机译:特征提取;武器本体;视觉/概念层次;收敛;武器识别;威胁评估;

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