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A multi-modal video analysis system

机译:多模式视频分析系统

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摘要

In this paper, we present a system for Chinese news program management based on cross media video analysis. Audio, caption text and video frames are all important for a person to understand the meaning of the video. Given these facts, we devised a system integrating continuous Chinese speech recognition (ASR), video caption text recognition (VOCR) and object/scene recognition (OR). The news program is firstly segmented to a serial of segments by anchor person detection. Then the ASR and VOCR recognition results are treated as two paragraphs of text, and we translate them to two bags of words to represent the original recognition results. By analysing the correspondance of the words in ASR result and VOCR result, we can get a trusted set of words to depict the video content of a segment of news program. In the last step, we implement the object/scene classification based on the keyframes analysis aided by the above recognition words. Experiments show that our news management system is efficient.
机译:在本文中,我们提出了一种基于跨媒体视频分析的中文新闻节目管理系统。音频,字幕文本和视频帧对于一个人理解视频的含义都很重要。鉴于这些事实,我们设计了一个集成了连续中文语音识别(ASR),视频字幕文本识别(VOCR)和对象/场景识别(OR)的系统。首先通过主持人检测将新闻节目分割成一系列片段。然后,将ASR和VOCR识别结果视为文本的两个段落,然后将它们翻译成两袋单词来表示原始识别结果。通过分析ASR结果和VOCR结果中单词的对应关系,我们可以获得一组值得信赖的单词来描述一段新闻节目的视频内容。在最后一步中,我们基于上述识别词的关键帧分析实现对象/场景分类。实验表明,我们的新闻管理系统是有效的。

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