Basketball Foul Tracking Method based on Video Detail Enhancement

In basketball matches, the referees are often the criteria for judging the fouls, but there are often disputes in the manual form of judging. Therefore, the study proposes a basketball game foul action tracking method based on video detail enhancement, which mainly consists of two parts: object detection and object tracking. Among them, the object detection part integrates wavelet transform, three frame difference method, and background subtraction method to achieve the detection of moving targets. In the object tracking section, the improved CamShift tracking algorithm and HMM are used to complete the tracking and recognition of target actions. The simulation experiment shows that the F-measure value of the tracking model is 0.89, the accuracy rate of foul action recognition reaches 99.76%, and the average error is only about 0.003. Therefore, the research-proposed basketball foul tracking method based on video detail enhancement has a good tracking effect, which can achieve the effect of accurate punishment in the basketball game and ensure the fairness of the game.