Application of Correlation Filter Tracking Algorithm Based on Multiple Color Features in Basketball Motion Capture System

The application of motion capture system in basketball game can intercept the highlights of the game and improve the viewing effect. In order to improve the tracking performance of target tracking algorithm and the efficiency of traditional basketball tracking system, a correlation filtering algorithm combining multiple color features is adopted in this study. A dhcf as algorithm based on multicolor feature is established. The adaptability of traditional KCF algorithm in scene attributes such as rapid target change and illumination change is mainly studied. The success rate of multicolor tracking algorithm can reach 78.2%. At the same time, based on the traditional kernel correlation filter, the algorithm combines the discriminant color descriptor and the direction gradient histogram. The results show that the success rate and accuracy of the algorithm in otb50 are 84.2% and 82.5%, respectively. In addition, excellent tracking performance is reflected in various scene attributes. Therefore, the algorithm can improve the target tracking performance of the traditional kernel correlation filter, especially solving the adaptability of the traditional algorithm in the scene of light change, fast target movement, and so on.

Automated summary

The application of motion capture system in basketball game can intercept the highlights of the game and improve the viewing effect. This study adopts a correlation filtering algorithm combining multiple color features to improve the tracking performance of target tracking algorithm and the efficiency of traditional basketball tracking system.