| Title |
Research on Tracking Athletes and Trajectory Analysis in Skiing with YOLO Algorithm and Kalman Filter |
| Authors |
(Xiaoguo Chang) ; (Wei Gao) |
| DOI |
https://doi.org/10.5573/IEIESPC.2026.15.2.176 |
| Keywords |
YOLO; Kalman filter; Halfpipe snowboard; Target tracking |
| Abstract |
U-shaped snowboard is one of the most popular events in the Winter Olympics. In order to optimize the key technical movements and skills of athletes in the competition, this paper presents a method based on YOLO algorithm and Kalman filter to detect and track athletes, and to predict and draw the movement curve of athletes in the competition, in order to analyze the posture and movement of athletes in the competition and establish a model to improve the performance and results of athletes in the competition. Under the condition of replicating the U-shaped ski field in the laboratory, the method can track the target replaced by the ball in real time, and use Kalman filter to recognize the target and predict the trajectory. The experimental results show that the method has high accuracy and speed in tracking the athletes’ competition scene, and can accurately draw the athletes’ movement trajectory in the replica model, which can basically meet the needs of analyzing athletes’ movements and skills. The proposed algorithm uses a dataset to verify its performance. On the data set, the detection accuracy of this paper is 83.4%.
Compared with the benchmark algorithm YOLOv4 (78.1%), the accuracy is improved by 5.3%, and the detection speed is 30.6 FPS. |