Automatic classification of tennis video for high-level content-based retrieval

G. Sudhir, J. C. Lee, Anil K. Jain
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引用次数: 254

Abstract

We present our techniques and results on automatic analysis of tennis video to facilitate content-based retrieval. Our approach is based on the generation of an image model for the tennis court-lines. We derive this model by using the knowledge about dimensions and connectivity (form) of a tennis court and typical camera geometry used when capturing a tennis video. We use this model to develop: a court line detection algorithm; and a robust player tracking algorithm to track the tennis players over the image sequence. We also present a color-based algorithm to select tennis court clips from an input raw footage of tennis video. Automatically extracted tennis court lines and the players' location information are analyzed in a high-level reasoning module and related to useful high-level tennis play events. Results on real tennis video data are presented demonstrating the validity and performance of the approach.
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基于高级内容检索的网球视频自动分类
我们提出了网球视频自动分析的技术和结果,以促进基于内容的检索。我们的方法是基于生成网球场线的图像模型。我们通过使用关于网球场的尺寸和连接(形式)的知识以及捕获网球视频时使用的典型摄像机几何形状来推导该模型。我们利用这个模型开发了:一个球场线检测算法;以及一个健壮的球员跟踪算法,通过图像序列跟踪网球运动员。我们还提出了一种基于颜色的算法,从输入的网球视频原始片段中选择网球场片段。自动提取的网球场线和球员的位置信息在高级推理模块中进行分析,并与有用的高水平网球比赛事件相关。通过对真实网球视频数据的分析,验证了该方法的有效性和有效性。
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