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A Novel RS-Based Key Frame Extraction Algorithm for Video Mining in Compressed-Domain

机译:基于RS的压缩域视频挖掘关键帧提取新算法

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摘要

It is a challenging issue to analyze video content for video mining tasks due to lacking of effective method to video analysis. In this paper, we propose a novel key frame extraction algorithm based on Rough Sets (RS) in Discrete Cosine Transform (DCT) compressed-domain. Firstly, we extract DCT coefficients in compressed-domain, select and preprocess the DC coefficients that derived from DCT coefficients. Secondly, we construct Information System with DC coefficients. Finally, we reduce Information System using attributes reduced theory of RS, and obtained the representation of the video frames by reduced DC coefficients. Experimental results show that the proposed algorithm is fast and effective. Compared to conventional algorithm, our algorithm enjoys the following advantages: (1) the numbers of the key frame extracted using our algorithm become more scientific; (2) the algorithm can avoid the expensive computations in decompression process.
机译:由于缺乏有效的视频分析方法,因此分析视频内容以进行视频挖掘任务是一个具有挑战性的问题。在本文中,我们提出了一种基于粗糙集(RS)的离散余弦变换(DCT)压缩域中的关键帧提取新算法。首先,我们在压缩域中提取DCT系数,选择和预处理从DCT系数得出的DC系数。其次,构建具有DC系数的信息系统。最后,我们利用RS的属性约简理论对信息系统进行约简,并通过降低DC系数得到视频帧的表示。实验结果表明,该算法是快速有效的。与常规算法相比,本算法具有以下优点:(1)使用本算法提取的关键帧的数量更加科学; (2)该算法可以避免解压缩过程中的昂贵计算。

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