足球比赛场景中交互行为分析方法研究

目前的视频处理研究主要关注足球视频的基础方面的问题, 而在视频语义方面的工作尚不完善。 为此, 对足球比赛视频中存在的交互行为进行分析, 研究了足球比赛视频语义理解的关键问题, 为实现从一般比赛场景去理解和分析比赛进行了有益的探索。 首先进行场景分析, 利用主颜色提取视频中场地区域并标定场地线; 其次, 检测场景中的球员并判定其队属, 同时利用 Kalman 滤波实现对足球目标的跟踪; 最后, 判定球队的进攻方向的目的语义, 同时获取足球真实轨迹, 进行轨迹分割, 识别球员与足球的交互行为, 并在此基础上结合足球领域的知识进行进攻策略的分析。 实验结果表明, 该算法能很好地解决视频分析各阶段的问题, 能有效分析视频中存在的交互行为, 并从足球领域的角度实现进攻策略分析,进攻模式识别结果查准率达到 71% 以上, 查全率达到 85% 以上, 有益于计算机视觉的应用研究和足球视频科学分析。

Research on Interactive Behavior Analysis for Soccer Video

Current research mainly focused on the basics of soccer video, and the work about video semantic analysis was not perfect. We analyzed the interaction behavior in soccer video, and the key problems of soccer video semantic understanding system were studied which made a useful exploration in understanding and analyzing the competition from a common scene. Firstly, the playfield was extracted from the video by using main color of the video and the field line was calibrated. Secondly, the players were detected and judged into the team they belonged to. Simultaneously, ball trajectory tracking was obtained by using Kalman filtering. Lastly, offensive goal of the players was judged, and the real trajectory of the ball was obtained and segmented. Then the offensive strategy was analyzed from the perspective of the soccer field based on the recognition of the interaction behavior between the ball and the players. Experiment results show that the proposed algorithm can effectively solve the problem of each stage in the video analysis and good performance is achieved from analyzing the interactions behavior existed in the video. And the analysis of the offensive strategy is realized from the perspective of the soccer field, the precision of the offense pattern recognition result was more than 71% and the recall rate was above 85%. Good achievements are obtained in both the application of computer vision research and the scientific research for soccer sports.