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Frame based approach for automatic event boundary detection of soccer video using optical flow

机译:基于帧的基于光流的足球视频事件边界自动检测方法

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Due to rapid growth of digital contents, there has been an increasing demand of summarized videos to save time and other network resources. Automated soccer video analysis is a challenging due to involvement of more actors and rapid movements of players and camera. It is necessary first to detect various events of the video precisely before analyzing and labeling them. This paper proposes frame based approach for the automatic demarcation of events of the soccer video. However this task is very challenging due to variety of soccer leagues, various illumination and ground conditions. To overcome such issues we propose method which is invariant to such conditions and can successfully demarcate the soccer events. We exploit optical flow techniques to measure the motion. We introduce change in optical flow to extract the behavior of an event over the video span. Later, adaptive threshold is computed based on change in optical flow. We conducted number of simulations with variety of videos to validate the method. Proposed method achieves nearly 90% of accuracy and found robust in spite of illumination variation.
机译:由于数字内容的快速增长,对摘要视频的需求不断增长,以节省时间和其他网络资源。由于更多演员的参与以及球员和摄像机的快速移动,自动足球视频分析是一项挑战。首先,必须在分析和标记视频之前准确检测视频的各种事件。本文提出了一种基于帧的足球视频事件自动标定方法。然而,由于足球联赛,照明和地面条件的变化,该任务非常具有挑战性。为了克服这些问题,我们提出了一种在这种情况下不变的方法,并且可以成功地划分足球事件。我们利用光流技术来测量运动。我们介绍了光流的变化,以提取视频范围内事件的行为。之后,基于光流的变化来计算自适应阈值。我们使用各种视频进行了多次仿真,以验证该方法。所提出的方法可达到近90%的精度,并且尽管存在光照变化,但仍具有鲁棒性。

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