Easy-to-use, General, and Accurate Multi-Kinect Calibration and its Application to Gait Monitoring for Fall Prediction

被引:0
|
作者
Staranowicz, Aaron N. [1 ]
Ray, Christopher [2 ]
Mariottini, Gian-Luca [1 ]
机构
[1] Univ Texas Arlington, Dept Comp Sci & Engn, ASTRA Robot Lab, 500 UTA Blvd, Arlington, TX 76019 USA
[2] Univ Texas Arlington, Dept Kinesiol, Arlington, TX 76019 USA
关键词
MORTALITY; INJURY;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Falls are the most-common causes of unintentional injury and death in older adults. Many clinics, hospitals, and health-care providers are urgently seeking accurate, low-cost, and easy-to-use technology to predict falls before they happen, e.g., by monitoring the human walking pattern (or "gait"). Despite the wide popularity of Microsoft's Kinect and the plethora of solutions for gait monitoring, no strategy has been proposed to date to allow non-expert users to calibrate the cameras, which is essential to accurately fuse the body motion observed by each camera in a single frame of reference. In this paper, we present a novel multi-Kinect calibration algorithm that has advanced features when compared to existing methods: 1) is easy to use, 2) it can be used in any generic Kinect arrangement, and 3) it provides accurate calibration. Extensive real-world experiments have been conducted to validate our algorithm and to compare its performance against other multi-Kinect calibration approaches, especially to show the improved estimate of gait parameters. Finally, a MATLAB Toolbox has been made publicly available for the entire research community.
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页码:4994 / 4998
页数:5
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