基于运动场的体育视频的镜头视图分类

Alfian Abdul Halin, M. Rajeswari, D. Ramachandram
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引用次数: 8

摘要

在本文中,我们提出了一种将基于操场的体育视频镜头分类到各自视图类的技术。根据常见的广播风格,一个镜头可以分为远视图和特写视图。该技术考虑HSV颜色空间中每个像素的逐帧颜色值,同时计算分割的游戏场区域内假设的对象大小。实验结果表明,该技术可以大大减少误分类次数,同时保持较好的准确率。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以运动场为基础的运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shot view classification for playfield-based sports video
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.
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