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Multimodal pattern matching for audio-visual query and retrieval

机译:用于视听查询和检索的多模式模式匹配

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摘要

A necessary capability for content-based retrieval is to support the paradigm of query by example. In the past, there have been several attempts to use low-level features for video retrieval. None of the approaches however uses the multimedia information content of the video. We present an algorithm for matching multimodal (audio-visual) patterns for the purpose of content-based video retrieval. The novel ability of our approach to use the information content in multiple media coupled with a strong emphasis on temporal similarity differentiates it from the state-of-the-art in content-based retrieval. At the core of the pattern matching scheme is a dynamic programming algorithm, which leads to a significant improvement in performance. Coupling the use of audio with video this algorithm can be applied to grouping of shots based on audio-visual similarity. This is much more effective in constructing scenes from shots than using only visual content to do the same.
机译:基于内容的检索的必要功能是通过示例支持查询范式。过去,曾有几次尝试使用低级功能进行视频检索。但是,没有一种方法使用视频的多媒体信息内容。为了基于内容的视频检索,我们提出了一种用于匹配多模式(视听)模式的算法。我们的方法在多种媒体中使用信息内容的新颖能力,以及对时间相似性的高度重视,使其与基于内容的检索技术脱颖而出。模式匹配方案的核心是动态编程算法,该算法可显着提高性能。将该音频与视频的使用结合起来,可以将该算法应用于基于视听相似性的镜头分组。与仅使用视觉内容进行拍摄相比,此方法在根据镜头构建场景方面更为有效。

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