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基于 Kinect 的虚拟健身跑锻炼系统

  

  1. 1. 上海大学上海电影学院,上海 200072;
    2. 上海电影特效工程技术研究中心,上海 200072;
    3. 伯恩茅斯大学创意技术系,英国 伯恩茅斯 BH12 5BB
  • 出版日期:2017-10-31 发布日期:2017-11-03
  • 基金资助:
    国家自然科学基金项目(61402278);上海市自然科学基金项目(14ZR1415800);上海市科委科技攻关项目(16511101302);上海大学电影学
    高峰学科项目

Virtual Running Exercise System Based on Kinect

  1. 1. Shanghai Film Academy, Shanghai University, Shanghai 200072, China;
    2. Shanghai Engineering Research Center of Motion Picture Special Effects, Shanghai 200072, China;
    3. Department of Creative Technology, University of Bournemouth, Fern Barrow Poole BH12 5BB, UK
  • Online:2017-10-31 Published:2017-11-03

摘要: 健身跑是体育运动中最常用的锻炼方式,不恰当的跑步方式,不仅达不到理想的健
身效果,而且很容易对身体特别是膝盖造成伤害。针对目前跑步系统缺乏科学指导和全程监测,
本文提出了一个基于 Kinect 的虚拟健身跑锻炼系统。在动作识别方面,通过角度特征和关节点相
对位置对 Kinect 采集的跑步动作信息进行降维,并分割出跑步动作元,利用动作元的曲线特征和
分类模型匹配,进行跑步动作识别,同时对跑步姿态进行科学指导。在运动建模方面,分析用户
心率和跑步强度的关系,构建用户的健身跑运动模型,并建立个性化科学跑步运动方案,使心率
始终处在安全有效的心率区间内。实验结果表明,该系统具有较强的实用性和可行性,能够为用
户进行安全、有效地健身跑锻炼提供科学的技术支持。

关键词: 体感交互, 健身跑, 动作识别, 运动建模

Abstract: Fitness running is a common exercise in sports. Due to the improper running form, it is not only
hard to reach the ideal fitness result, but also easy to harm the body seriously, especially the knee. To
address the problems of lacking scientific guidance and monitoring in current running systems, this paper
proposed a virtual running exercise system based on Kinect. In the action recognition, the dimension of
running data collected from Kinect is reduced according to the angle characteristics and the relative
position of human joints, and running action units are divided from motion features set. Then all kinds of
running actions are recognized by matching with curve characteristics of action units and classification
models. In addition, scientific guidance about their running poses is given to users while exercise. In the
motion modeling, we analyze the relationship between the heart rate and running intensity, and build the
fitness running model and the individualized scientific running exercise scheme, making the heart rate
always in the safe and effective range. The experiment results show that our system is practical and
feasible to provide a scientific method for safe and effective fitness running to users.

Key words: somatosensory interaction, fitness running, action recognition, motion modeling