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Video news face retrieval based on Web image datasets

机译:视频新闻面部检索基于Web映像数据集

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Automatic annotation of broadcasting news programs is a challenging task for multimedia press review. Usually in a video stream, the head of a person moves continuously and changes in facial expressions, lighting conditions, and camera motion produce significant distortions in the image appearance that can largely affect recognition performances. In this paper a system for automatic face identification in TV broadcasting programs is proposed. The proposed approach is based on a joint use of Scale Invariant Feature Transform descriptor and Eigenfaces-based approach. The algorithm has been tested on two national broadcasting channels. Experimental results show that the joint use of these two approaches improves the recognition rate.
机译:广播新闻节目的自动注释是多媒体新闻评论的具有挑战性的任务。通常在视频流中,人的头部连续移动,并且在面部表情,照明条件和相机运动中的变化产生显着的图像外观,这些图像外观可能在很大程度上影响识别性能。在本文中,提出了一种在电视广播节目中自动面部识别系统。所提出的方法基于对基于规模不变特征变换描述符和基于特征的方法的联合使用。该算法已经在两个国家广播渠道上进行了测试。实验结果表明,这两种方法的关节使用提高了识别率。

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