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A Knowledge Engineering Approach for Complex Violence Identification in Movies

机译:一种关于电影复杂暴力识别的知识工程方法

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Along with the rapid increase of available multimedia data, comes the proliferation of objectionable content such as violence and pornography. We need efficient tools for automatically identifying, classifying and filtering out harmful or undesirable video content for the protection of sensitive user groups (e.g. children). In this paper we present a multimodal approach towards the identification and semantic analysis of violent content in video data. We propose a layered architecture and focus on ontological and knowledge engineering aspects of video analysis. We demonstrate the development of two ontologies defining violent hints hierarchy that low level analysis, in visual and audio modality, respectively should identify. Violence domain ontology, as a reality representation, defines higher-level semantics. Taking under consideration extracted violent hints, spatio-temporal relations and behavior patterns higher-level semantics automatic inference is possible.
机译:随着可用多媒体数据的快速增加,令人反感的内容(如暴力和色情)的扩散。我们需要有效的工具,用于自动识别,分类和过滤禁止保护敏感用户组的有害或不良视频内容(例如儿童)。在本文中,我们提出了一种多模式方法,朝着视频数据中的暴力内容的识别和语义分析。我们提出了分层体系结构,专注于视频分析的本体学和知识工程方面。我们展示了在视觉和音频模型中展示定义暴力提示层次结构的两个本体的发展,即应识别。暴力域本体作为现实表示,定义了更高级别的语义。正在考虑提取的暴力提示,时空关系和行为模式可以自动推理更高级别的语义。

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