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Application of randomized algorithm in key frames extraction

机译:随机算法在关键帧提取中的应用

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With the application of multimedia information, a large amount of video information comes forth, how to retrieval the information required from the vast amount of data is vital. Content-based Video Retrieval is one of the leading methods to get the needed information from the vast amount of video data. Technology to extract key frames, which is an important part of content-based video retrieval, was studied carefully. In the compressed domain environment, firstly divide the two frames to be compared into sub-blocks, and then use randomized algorithm to select a subset of the divided sub-blocks to calculate similarity, and then to select key frames. The method can be guaranteed to meet the inter-frame similarity calculation under a certain precision, significantly reducing the number of sub-blocks needed to compare, thereby enhancing operational efficiency of the algorithm, and experimental results proved to be better.
机译:随着多媒体信息的应用,大量的视频信息应运而生,如何从大量的数据中检索所需的信息至关重要。基于内容的视频检索是从大量视频数据中获取所需信息的主要方法之一。认真研究了提取关键帧的技术,该技术是基于内容的视频检索的重要组成部分。在压缩域环境中,首先将要比较的两个帧划分为子块,然后使用随机算法选择划分后的子块的一个子集来计算相似度,然后选择关键帧。该方法可以保证在一定的精度下满足帧间相似度计算,大大减少了比较所需的子块数,从而提高了算法的运算效率,实验结果证明是较好的。

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