A study of student movement characteristics in college soccer teaching based on motion capture technology

Motion capture technology is a revolutionary technology that can bring great development to soccer. In this paper, a motion capture system with wearable inertial sensors is used to collect, decompose and process students’ soccer movement data, and establish a 3D human posture model based on the data to restore and analyze students’ soccer movement characteristics. The validity of the 3D human posture model is verified by the 3D human posture reconstruction result test, and the accuracy of the SVM algorithm is verified by the soccer action recognition and data acquisition experiments. The 3D human posture model selected in this paper can more accurately restore human movement characteristics compared to other methods, and the SVM algorithm achieves 100% accuracy in soccer movement recognition experiments. The application of motion capture technology to the study of students’ movement characteristics in college soccer teaching can help soccer teaching move away from relying solely on experience and enter the digital era.