Literature DB >> 26737413

Easy-to-use, general, and accurate multi-Kinect calibration and its application to gait monitoring for fall prediction.

Aaron N Staranowicz, Christopher Ray, Gian-Luca Mariottini.   

Abstract

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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Year:  2015        PMID: 26737413     DOI: 10.1109/EMBC.2015.7319513

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Validation of enhanced kinect sensor based motion capturing for gait assessment.

Authors:  Björn Müller; Winfried Ilg; Martin A Giese; Nicolas Ludolph
Journal:  PLoS One       Date:  2017-04-14       Impact factor: 3.240

2.  A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks.

Authors:  Po-Chang Su; Ju Shen; Wanxin Xu; Sen-Ching S Cheung; Ying Luo
Journal:  Sensors (Basel)       Date:  2018-01-15       Impact factor: 3.576

  2 in total

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