Sports Video Motion Target Detection and Tracking Based on Hidden Markov Model

摘要

Sports video moving object detection and tracking is a hot topic in computer vision research. The hidden Markov model is applied to the detection and tracking of moving objects in sports video. The acquired student motion is used as input to interact with the virtual scene. Firstly, the virtual and real difference measurement selection algorithm based on statistics is used to select the sports students with strong ability. Then, the classifier confidence method is used to select the students with high confidence level from the sports students who have not been marked, and classify them into the marked sports students to promote the generalization ability of the model. Raise. The experimental results show that this method can effectively assist physical education teaching activities and provide objective and effective data analysis for sports video target detection and tracking.