一种鲁棒的场地球类视频中的球门探测方法

在场地球类视频中,球门常常会伴随着精彩片段而出现。因此,球门探测是体育视频的基础,同时也是视频高层语义概念探测的研究热点。目前,利用机器学习方法进行视频中的对象探测是非常有前途的研究领域。基于此,提出一种基于模糊决策树的球门探测算法,用来探测场地球类视频中球门帧的出现,为了提高分类准确性,在模糊决策树训练的过程中加入了平衡处理。实验结果表明,与基于阈值和决策树的算法相比,该算法可以得到更好的分类结果(F-measure>95%),并且我们可以从所建立的树中推导出模糊规则来解释分类模型。

A robust goalmouth detection method in field-ball game video

Recently, goalmouth detection has become the basis of highlight summarization and a hot topic in high-level semantic concept detection, as the appearance of goalmouth indicates a high likelihood of exciting action in field-ball game video. In addition, machine learning for object detection is a promising research frontier. In this paper, a robust method is proposed to detect the presence of goalmouth frame in field-ball game video based on fuzzy decision trees. Balance process is added in training procedure. The experimental results show that our algorithm (F-measure>95%) can improve the classification performance when comparing with the threshold based algorithm and the decision tree based algorithm. Fuzzy rules can also be easily deduced from the constructed tree to interpret the classification model.