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Automatic Textual Annotation Of Video News Based on Semantic Visual Object Extraction

机译:基于语义视觉对象提取的视频新闻自动文本注释

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摘要

In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.
机译:在本文中,我们介绍了基于视频新闻的可视内容分析自动生成文本元数据的工作。我们提出了两种用于从交叉模态图像-文本同义词库进行语义对象检测和识别的方法。这些同义词库表示模型和语义标签之间的监督关联。本文涉及两个语义对象:人脸和电视徽标。在第一部分中,我们介绍了通过自动名称生成进行有效面部检测和识别的工作。该方法还允许我们建议镜头特写估计的文本注释。另一方面,我们有兴趣自动检测和识别出现在来自不同电视频道的不同新闻中的不同电视徽标。这项工作是与“ MediaWorks”项目中的法国电视频道TF1共同完成的,该项目包括视频新闻的混合文本图像索引和检索平台。

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