基于机器视觉的身体健康测量与人体姿势识别和骨骼数据平滑

Xuelian Cheng, Mingyi He, Weijun Duan
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引用次数: 5

摘要

设计并实现了一种基于机器视觉的身体素质测量系统。与其他现有系统相比,我们的系统只使用一个Kinect传感器,没有笨重的可穿戴传感器,从而使测试者灵活自由。为了提高测试精度,开发或使用了一系列骨骼数据平滑方法和姿态识别算法。在大学生中进行的测试和实验结果表明,该系统的性能得到了提高,与人类的性能相当,因此更加实用和省力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine vision based physical fitness measurement with human posture recognition and skeletal data smoothing
A machine vision based measurement system for physical fitness is designed and implemented. Compared with other existing systems, our system only utilizes one Kinect sensor without bulky wearable sensors, thus enabling testees limber and free. To improve the test accuracy, a series of skeletal data smoothing methods and posture recognition algorithms are developed or used. The tests among university students and experimental results show that the performance of our system is increased and it is comparable with human beings, and therefore more practical and labor-saving.
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