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Cricket activity detection

机译:板球活动检测

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摘要

Cricket broadcast video analysis has had difficulty identifying aspects of the content such as the type of batting stroke or the direction of the field played towards. Here we construct a composite feature combining Optical flow analysis along with camera view analysis to model the type of shots played. The work first presents an improved camera shot analysis based on learning parameters from a small supervision set. This splits the broadcast video into shots which are combined into balls and, the segment where the batsman is playing the stroke is identified. After that optical flow analysis is used to determine the direction of the stroke with an accuracy of 80 percent.
机译:板球广播视频分析难以识别内容的各个方面,例如击球的类型或比赛方向。在这里,我们构建了一个结合了光流分析和相机视图分析的复合特征,以模拟镜头的类型。这项工作首先提出了一个改进的摄像机镜头分析方法,该方法基于来自小型监督集的学习参数。这会将广播视频分成多个镜头,然后将这些镜头组合成多个球,并识别出击球手打球的片段。之后,使用光流分析以80%的精度确定冲程方向。

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