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Internet Video Search and Repurposing through Face Analysis

机译:通过脸部分析进行互联网视频搜索和重新定位

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With the ever-growing amount of videos on the internet, searching for desired videos in an effective and efficient way remains a challenge. In addition, repurposing videos of interest into new attractive photo/video products has been an open issue. In this paper, we propose a framework for video retrieval and repurposing by leveraging the face information in videos. Since text query cannot express user's intent precisely and it may generate noisy result, an automatic query image generation method is proposed to provide user with visual and intuitive candidate images. Then, based on user-selected query image, videos are re-ranked through content analysis so that videos with higher relevance can emerge to the top. Furthermore, relevant segments and frames are obtained and they can be used to compose customized photo/video products, which provides user with a fresh experience as a creator. In this paper, a prototype of video retrieval and repurposing system is implemented for retrieving videos of celebrities and generating customized products. Experiments have been done on 3416 video clips related to about 103 celebrities downloaded from YouTube. The experimental results show the effectiveness of our proposed method.
机译:随着互联网上视频数量的不断增长,以有效和高效的方式搜索所需的视频仍然是一个挑战。另外,将感兴趣的视频重新用于新的有吸引力的照片/视频产品中是一个未解决的问题。在本文中,我们提出了一个利用视频中的面部信息进行视频检索和重新定位的框架。由于文本查询无法准确表达用户的意图,并且可能产生嘈杂的结果,因此提出了一种自动查询图像生成方法,为用户提供了直观直观的候选图像。然后,基于用户选择的查询图像,通过内容分析对视频进行重新排名,从而使具有较高相关性的视频出现在顶部。此外,获得了相关的片段和框架,它们可以用于组成定制的照片/视频产品,从而为用户提供了创作者的新鲜体验。本文实现了一种视频检索与重用系统的原型,用于检索名人视频并生成定制产品。已对从YouTube下载的约103名名人相关的3416个视频片段进行了实验。实验结果表明了该方法的有效性。

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