Performance analysis of sports training based on random forest algorithm and infrared motion capture

Abstract

Because sports video has a wide audience and huge market potential, research with the main goal of sports video content analysis has become a hot spot in the field of video analysis. Although after more than ten years of hard work, the current achievements are still far from the expectations of people. In this study, the sports video is taken as the analysis object, and for the shortcoming that when the VIRE positioning algorithm uses linear interpolation to calculate the virtual label, the error between the obtained RSSI value and the actual value is larger, this paper uses quadratic interpolation to improve it. Moreover, this study explores the threshold setting of the algorithm and proposes a threshold setting method, so that the adjacent map thresholds of each reader are not necessarily consistent, and the resulting adjacent label map is more accurate. In addition, this experiment uses the algorithm model designed in this study combined with the qualysis infrared capture system to capture the tennis serve. Finally, this study conducts model algorithm performance analysis through comparative analysis. The research results show that the algorithm of this study has certain practical effects.