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Effective algorithm for detecting various wipe patterns and discriminating wipe from object and camera motion

机译:用于检测各种划像图案并将划像与物体和相机运动区分开的有效算法

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摘要

Wipe transition detection in video segmentation is more difficult to detect than abrupt and other gradual transitions, because of diversity in patterns, and difficulty in distinguishing wipe from camera and object motion. In this study, the authors propose an algorithm for wipe transition detection. In the proposed algorithm, first the moving strip due to wipe is obtained, which eliminate most of the edges due to object boundaries and retain true wipe boundaries, and then Hough transform is applied on these moving lines to detect and categorise various wipe types. In order to decrease the computational load of the proposed algorithm, the authors propose a preprocessing step as a first stage of the algorithm. The preprocessing step consists of calculation of statistical image difference between the consecutive frames to obtain the potential wipe frames, which are input to their proposed algorithm. The proposed algorithm detects and identifies various types of wipes and also distinguishes wipes from object and camera motion. The performance comparison of the proposed algorithm, with and without preprocessing, with other existing techniques clearly exhibit its effectiveness in terms of better recall, precision, F1 measure and detection rate.
机译:视频分割中的划像过渡检测比突然过渡和其他渐进过渡更难检测,这是因为图案的多样性以及难以将划像与摄像机和物体运动区分开。在这项研究中,作者提出了一种擦除过渡检测算法。在提出的算法中,首先获得由于擦拭而产生的运动带,该运动带消除了由于对象边界引起的大部分边缘并保留了真实的擦拭边界,然后在这些运动线上应用了霍夫变换来检测和分类各种擦拭类型。为了减轻所提出算法的计算负担,作者提出了预处理步骤作为算法的第一阶段。预处理步骤包括计算连续帧之间的统计图像差异,以获得潜在的划像帧,然后将其输入到提出的算法中。提出的算法可以检测和识别各种类型的擦拭,还可以将擦拭与物体和相机运动区分开。该算法在进行预处理和不进行预处理的情况下与其他现有技术的性能比较,清楚地显示了其在更好的查全率,精度,F1测量和检测率方面的有效性。

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  • 来源
    《Image Processing, IET》 |2010年第6期|p.429-442|共14页
  • 作者单位

    SPANN Laboratory, Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India;

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