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A Knowledge Engineering Approach for Complex Violence Identification in Movies

机译:电影中复杂暴力识别的知识工程方法

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摘要

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迅速增加,令人反感的内容(如暴力和色情内容)的泛滥也随之而来。我们需要高效的工具来自动识别,分类和过滤有害或不良视频内容,以保护敏感的用户组(例如儿童)。在本文中,我们提出了一种用于识别和语义分析视频数据中暴力内容的多模式方法。我们提出了一个分层的体系结构,并专注于视频分析的本体和知识工程方面。我们演示了定义暴力提示层次结构的两种本体的发展,低级分析(分别在视觉和音频模态中)应该识别这种暴力提示层次结构。暴力域本体作为一种现实表示,定义了更高级别的语义。考虑到提取的暴力提示,时空关系和行为模式,高层语义自动推断是可能的。

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