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首页> 外文期刊>EURASIP journal on advances in signal processing >Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection
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Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection

机译:使用QR分解和高斯跃迁检测的视频镜头边界检测

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This article explores the problem of video shot boundary detection and examines a novel shot boundary detection algorithm by using QR-decomposition and modeling of gradual transitions by Gaussian functions. Specifically, the authors attend to the challenges of detecting gradual shots and extracting appropriate spatiotemporal features that affect the ability of algorithms to efficiently detect shot boundaries. The algorithm utilizes the properties of QR-decomposition and extracts a block-wise probability function that illustrates the probability of video frames to be in shot transitions. The probability function has abrupt changes in hard cut transitions, and semi-Gaussian behavior in gradual transitions. The algorithm detects these transitions by analyzing the probability function. Finally, we will report the results of the experiments using large-scale test sets provided by the TRECVID 2006, which has assessments for hard cut and gradual shot boundary detection. These results confirm the high performance of the proposed algorithm.
机译:本文探讨了视频镜头边界检测的问题,并研究了一种新颖的镜头边界检测算法,该算法使用QR分解和高斯函数对渐变过渡进行建模。特别是,作者们面临着检测渐进镜头和提取适当时空特征的挑战,这些特征会影响算法有效检测镜头边界的能力。该算法利用了QR分解的特性,并提取了逐块概率函数,该函数说明了视频帧处于镜头过渡的概率。概率函数在硬切换中具有突变,在渐变中具有半高斯行为。该算法通过分析概率函数来检测这些转换。最后,我们将使用TRECVID 2006提供的大规模测试集报告实验结果,该测试集对硬切和渐进式镜头边界检测进行了评估。这些结果证实了所提出算法的高性能。

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