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Evaluating Strategies and Systems for COntnet Based Indexing of Person Images on the Web

机译:基于内容的内容索引在Web上的评估策略和系统

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Content based indexing of multimedia has alwasy been a challenging task. THe enormity and the diversity of the multimedia content on the web adds another dimension to this challenge. In this paper, we examine ways of combining visual and textual information for contetn based indexing of multimedia on the web. In particular, wer examine different metods of combining evidences due to face detection, Text/HTML analysis and face recogntiion for identifying person images. We provide experiemntal evaluation of the following strategies: i) Face detection on the image followed by Text/HTML nalaysis of the containing apge; ii) face detection followed by face recognition; iii) face detection followed by a linear combination of evidences due to text/HTML anlaysis and face recognition; and iv) face detection followed by a Dempster-Shafer combination of evidences due to text/HTML analysis and face recognition.
机译:基于内容的多媒体索引一直是一项艰巨的任务。 Web上的巨大内容和多样化的多媒体内容为这一挑战增加了另一个层面。在本文中,我们研究了将视觉和文本信息相结合的方法,以基于竞争性地在网络上对多媒体进行索引。特别是,由于面部识别,文本/ HTML分析以及用于识别人物图像的面部识别,我们将研究组合证据的不同方法。我们提供以下策略的实验性评估:i)在图像上进行面部检测,然后对包含的顶点进行Text / HTML修饰; ii)人脸检测后再进行人脸识别; iii)面部检测,然后由于文本/ HTML分析和面部识别而线性组合证据; iv)由于文本/ HTML分析和面部识别,面部检测之后是证据的Dempster-Shafer组合。

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