计算机科学 ›› 2023, Vol. 50 ›› Issue (3): 181-190.doi: 10.11896/jsjkx.220300062

• 计算机图形学&多媒体 • 上一篇    下一篇

基于规则推理的足球视频任意球射门事件检测

华晓凤1, 冯娜1, 于俊清1,2, 何云峰1   

  1. 1 华中科技大学计算机科学与技术学院 武汉 430074
    2 华中科技大学网络与计算中心 武汉 430074
  • 收稿日期:2022-03-07 修回日期:2022-05-21 出版日期:2023-03-15 发布日期:2023-03-15
  • 通讯作者: 于俊清(yjqing@hust.edu.cn)
  • 作者简介:(fengna@hust.edu.cn)

Shooting Event Detection of Free Kick in Soccer Video Based on Rule Reasoning

HUA Xiaofeng1, FENG Na1, YU Junqing1,2, HE Yunfeng1   

  1. 1 School of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan 430074,China
    2 Network and Computing Center of Huazhong University of Science and Technology,Wuhan 430074,China
  • Received:2022-03-07 Revised:2022-05-21 Online:2023-03-15 Published:2023-03-15
  • About author:HUA Xiaofeng,born in 1996,postgra-duate.Her main research interest is soccer video event detection.
    YU Junqing,born in 1975,Ph.D,professor,Ph.D supervisor.His main research interests include content-based video analysis,indexing and retrieval,multi-core computing and stream compilation,video emotion computing,network security and big data processing.

摘要: 足球视频事件检测对视频检索具有重要意义。然而,足球视频中事件较少,且主要发生在远镜头中,难以捕捉关键球员和关键动作,导致足球事件检测困难。近年来,基于深度学习的方法在足球视频事件检测上取得了一定的进展,但对事件的高层语义学习仍不够充分,检测结果有待进一步提高。如何提升足球视频事件检测的准确性是亟待解决的问题。以任意球射门事件为研究对象,提出了足球规则与深度学习相结合的事件检测模型。为了深入了解任意球射门事件的内在特性,人工总结了事件规则并在公共足球数据集上进行了验证,同时提出了规则的应用场景。针对足球视频中事件过少的问题,设计了基于规则的初始定位算法对视频进行预处理。通过多规则组合和应用,从原始视频中初步定位可能发生任意球射门事件的位置,并将其作为深度学习模型的输入进行进一步预测。在公共足球数据集上将所提模型与其他模型进行对比实验。结果表明,该模型取得了最好的效果,其精确率达到78%,召回率达到81.25%。相比其他模型,其精确率的提升尤为明显。可见,足球规则与深度学习相结合的任意球事件检测模型有效提升了任意球射门事件的检测性能,为足球视频中其他事件的检测提供了参考依据。

关键词: 足球视频, 任意球射门, 事件检测, 足球规则, 深度学习

Abstract: Soccer video event detection is of great significance to video retrieval.However,there are fewer events in soccer videos,and these events mainly occur in the far-view shot,which makes it difficult to capture key players and key actions,making soccer event detection more difficult.In recent years,methods based on deep learning have made some progress in soccer video event detection,but the learning ability of the high-level semantic of the event is still insufficient and the detection results need to be further improved.Therefore,how to improve the accuracy of soccer video event detection is an urgent problem to be solved.Taking the shooting event of free kick(free-kick shot event) as the research object,an event detection model combining soccer rules and deep learning is proposed.To have a deeper understanding of the inherent characteristics of the free-kick shot event,the event rules are manually summarized and verified on the public soccer dataset,and the corresponding application scenarios are also proposed.For the problem of too few events in soccer videos,rule-based initial localization algorithm is proposed to preprocess the videos.Through the combination and application of multiple rules,the location where the free-kick shot event may occur is initially located from the original video,which is used as the input of the deep learning model for further prediction.The proposed mo-del is compared with other models on the public soccer dataset.Experimental results show that the proposed model achieves the best results,with the accuracy rate of 78% and the recall rate of 81.25%.Compared with other models,the improvement in accuracy is particularly prominent.It can be seen that the free-kick shot event detection model that combines soccer rules and deep learning effectively improves the performance of free-kick shot event detection and provides a basic reference for further research on the detection of other events in soccer videos.

Key words: Soccer video, Free-kick shot, Event detection, Soccer rules, Deep learning

中图分类号: 

  • TP181
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