Soccer Goal Detection with Fusion Normalized Semantic Weighted Sum Rules

A normalized semantic weighted sum soccer goal detection fusion scheme is proposed in this paper.First,the hidden Markov model(HMM) for the goal event is constructed.Second,a new feature of semantic observation weights for the shots is proposed.With this new feature,a new manual rule,named normalized semantic weighted sum rule,is established.The goal event detection in soccer videos is implemented based on the HMM method and the normalized semantic weighted sum rule method,respectively.Finally,a fusion scheme based on the logic distance is proposed,which carries out the decision-level fusion with the optimal weights to fuse the HMM and the rule detection results,and significantly improves the performance of the goal event detection.The normalized semantic weighted sum rule proposed in this scheme uses of the statistical video information objectively,relies less on manual subjective observations,and overcomes the huge manual efforts in existing methods.It does not require complex training and the computational cost are relatively small.The experiments validate of effectiveness of this scheme.