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Characteristics Extraction of Behavior of Multiplayers in Video Football Game

机译：视频足球比赛多人游戏行为的特点提取

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摘要

In the process of behavior recognition of multiplayers for soccer game video, various features of athletes need to be extracted. In this paper, color moments extracted by using color classification learning set are regarded as color feature. Contour features of athletes are extracted by utilizing players silhouettes block extraction and normalization. Hough transform is used to extract the features of coordinates of pitch line, which can be used for camera calibration, rebuilding the stadium, and calculating the coordinate of players in the real scene. The trajectories of players and ball are predicted by using Kalman filter, while trajectories characteristics of player and ball are extracted by using the trajectory growth method. Temporal and spatial interest points are extracted in this paper. Experimental results show that the accuracy of behavior recognition can be greatly improved when these features extracted are used to recognize athlete behavior.
机译：在足球游戏视频的多人行为识别过程中，需要提取运动员的各种特征。在本文中，通过使用颜色分类学习集提取的颜色矩被视为彩色特征。通过利用球员剪影块提取和标准化来提取运动员的轮廓特征。 Hough变换用于提取音高线坐标的特征，可用于相机校准，重建体育场，并计算实际场景中的玩家的坐标。通过使用卡尔曼滤波器来预测玩家和球的轨迹，而通过使用轨迹生长方法提取播放器和球的轨迹特性。本文提取了时间和空间兴趣点。实验结果表明，当提取的这些特征用于识别运动员行为时，可以大大提高行为识别的准确性。

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