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Shot view classification for playfield-based sports video

机译:基于运动场的体育视频的镜头视图分类

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In this paper, we propose a technique for classifying shots of playfield-based sports video into their respective view classes. Based on common broadcasting style, a shot can be classified as a far-view or a closeup-view. The technique considers the frame-wise color values of each pixel in the HSV color space, while at the same time calculating the assumed object size within the segmented playfield region. Based on our experiments, it is shown that this technique can greatly reduce the number of misclassified shots, while at the same time maintain a good level of accuracy. At the moment, we have tested our approach on soccer videos but believe that it can be applied to other playfield-based sports as well.
机译:在本文中,我们提出了一种技术,用于将基于运动场的体育视频的镜头分类为各自的视图类。根据常见的广播样式,可以将镜头分为远景或近景。该技术考虑了HSV颜色空间中每个像素的逐帧颜色值,同时计算了分段运动场区域内的假定对象大小。根据我们的实验表明,该技术可以大大减少误分类的镜头数量,同时保持良好的准确性。目前,我们已经在足球视频上测试了我们的方法,但相信它也可以应用于其他基于运动场的运动。

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