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Reading Two Digital Video Clocks for Broadcast Basketball Videos

机译:读取两个数字视频时钟以播放篮球录像

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This paper presents an algorithm for reading two digital video clocks of broadcast basketball videos by using context-aware pixel periodicity method and deep learning technique. Reading two digital video clocks is a very challenge problem as a difficulty special case of reading video text. The first challenge task is the clock digit localization. The existing pixel periodicity is a very good method for localizing second-digit place if a single clock is in video, but it is not applicable to localizing two second-digit places. This paper proposes a context-aware pixel periodicity method to identify the second-pixels of each clock based on the domain knowledge of digital video clocks. The second challenge task is clock-digit recognition. For this task, the CNN-based procedures are proposed to recognize clock digits. The experimental results show that the proposed algorithm can achieve 100% of accuracy in both localization and recognition for two clocks at very low computational cost by using very short input clips.
机译:本文提出了一种使用上下文感知像素周期性方法和深度学习技术读取广播篮球视频的两个数字视频时钟的算法。读取两个数字视频时钟是一个非常具有挑战性的问题,这是读取视频文本的特殊困难情况。第一个挑战任务是时钟数字本地化。如果单个时钟位于视频中,则现有的像素周期性是一种很好的方法来定位第二个数字位置,但是不适用于本地化两个第二个数字位置。本文提出了一种基于上下文的像素周期性方法,该方法基于数​​字视频时钟的领域知识来识别每个时钟的第二个像素。第二项挑战任务是时钟数字识别。为此,建议使用基于CNN的程序来识别时钟数字。实验结果表明,通过使用非常短的输入片段,该算法可以以非常低的计算成本在两个时钟的定位和识别方面达到100%的精度。

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