计算机科学 ›› 2023, Vol. 50 ›› Issue (3): 181-190.doi: 10.11896/jsjkx.220300062
华晓凤1, 冯娜1, 于俊清1,2, 何云峰1
HUA Xiaofeng1, FENG Na1, YU Junqing1,2, HE Yunfeng1
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。
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