技术进步扩大了捕获人体运动的方法范围,包括涉及惯性传感器(IMU)和光学替代品的解决方案。然而,与商业解决方案相关的复杂性和成本不断上升,促使人们探索更具成本效益的替代方案。本文介绍了一种使用RealSense深度相机和智能计算机视觉算法的无标记光学运动捕获系统。它有助于精确的姿势评估,关节角度的实时计算,以及获取特定受试者的人体测量数据以进行步态分析。与复杂的商业解决方案相比,所提出的系统以其简单性和可负担性而著称。收集的数据存储在逗号分隔值(CSV)文件中,简化后续分析和数据挖掘。初步试验,在受控的实验室环境中进行,并采用商用MEMS-IMU系统作为参考,人体测量的最大相对误差为7.6%,平均高度最大绝对误差为4.67cm。步幅长度测量显示最大相对误差为11.2%。静态接头角度试验的最大平均误差为10.2%,而动态接头角度测试显示最大平均误差为9.06%。所提出的光学系统为康复等领域的潜在应用提供了足够的精度,体育分析,和娱乐。
Technological advancements have expanded the range of methods for capturing human body motion, including solutions involving inertial sensors (IMUs) and optical alternatives. However, the rising complexity and costs associated with commercial solutions have prompted the exploration of more cost-effective alternatives. This paper presents a markerless optical motion capture system using a
RealSense depth camera and intelligent computer vision algorithms. It facilitates precise posture assessment, the real-time calculation of joint angles, and acquisition of subject-specific anthropometric data for gait analysis. The proposed system stands out for its simplicity and affordability in comparison to complex commercial solutions. The gathered data are stored in comma-separated value (CSV) files, simplifying subsequent analysis and data mining. Preliminary tests, conducted in controlled laboratory environments and employing a commercial MEMS-IMU system as a reference, revealed a maximum relative error of 7.6% in anthropometric measurements, with a maximum absolute error of 4.67 cm at average height. Stride length measurements showed a maximum relative error of 11.2%. Static joint angle tests had a maximum average error of 10.2%, while dynamic joint angle tests showed a maximum average error of 9.06%. The proposed optical system offers sufficient accuracy for potential application in areas such as rehabilitation, sports analysis, and entertainment.