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Sports game teaching and high precision sports training system based on virtual reality technology
Entertainment Computing ( IF 2.8 ) Pub Date : 2024-03-24 , DOI: 10.1016/j.entcom.2024.100662
Yang Pan

Sports can combine virtual reality technology with high-precision training to enhance the training effectiveness of users. In view of the current problems of insufficient physical quality and lack of exercise motivation faced by college students, this paper aims to explore a new type of college sports game teaching model through the integration of virtual reality technology. This is to improve students 'physical exercise efficiency and subjective initiative. This study constructed an experiential sports game model by applying posture recognition technology and fuzzy comprehensive evaluation method. The research indicated that the error accuracy with residual structure added will quickly decrease. When calculating the error, the overall error decreased by 6 mm. The proposed method can accurately distinguish human behavior in motion and trajectories in the motion area. The motion capture accuracy was high, and the deformation amount met the teaching needs of higher education institutions for sports game teaching. The contribution of this study is the significant improvement in the accuracy of motion capture, resulting in a total error reduction to 6 mm. This improvement ensured that the model can accurately distinguish between motion behavior and trajectory. The cumulative variance explanation rate of the scale reached 712.407 %, which was far more than that of the traditional model, and fully covered and explained the questionnaire information. Through the comparative test with four knowledge tracking models, the effectiveness and superiority of the sports game teaching mode integrated with virtual reality technology were verified.

中文翻译:

基于虚拟现实技术的体育比赛教学与高精度运动训练系统

体育运动可以将虚拟现实技术与高精度训练相结合,提升用户的训练效果。针对当前大学生身体素质不足、运动动力缺乏的问题,本文旨在通过融合虚拟现实技术,探索一种新型的大学体育游戏教学模式。这是为了提高学生体育锻炼的效率和主观能动性。本研究应用姿势识别技术和模糊综合评价方法构建了体验式运动游戏模型。研究表明,加入残差结构后,误差精度会迅速下降。计算误差时,总体误差减少了6毫米。该方法可以准确地区分人类运动行为和运动区域的轨迹。动作捕捉精度高,变形量满足高等院校体育比赛教学的教学需求。这项研究的贡献在于显着提高了运动捕捉的准确性,使总误差降低至 6 毫米。这一改进确保了模型能够准确地区分运动行为和轨迹。该量表的累积方差解释率达到712.407%,远远超过传统模型,充分覆盖和解释了问卷信息。通过四种知识追踪模型的对比测试,验证了融合虚拟现实技术的体育游戏教学模式的有效性和优越性。
更新日期:2024-03-24
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