Literature DB >> 29678420

A novel validation and calibration method for motion capture systems based on micro-triangulation.

Gergely Nagymáté1, Tamás Tuchband2, Rita M Kiss3.   

Abstract

Motion capture systems are widely used to measure human kinematics. Nevertheless, users must consider system errors when evaluating their results. Most validation techniques for these systems are based on relative distance and displacement measurements. In contrast, our study aimed to analyse the absolute volume accuracy of optical motion capture systems by means of engineering surveying reference measurement of the marker coordinates (uncertainty: 0.75 mm). The method is exemplified on an 18 camera OptiTrack Flex13 motion capture system. The absolute accuracy was defined by the root mean square error (RMSE) between the coordinates measured by the camera system and by engineering surveying (micro-triangulation). The original RMSE of 1.82 mm due to scaling error was managed to be reduced to 0.77 mm while the correlation of errors to their distance from the origin reduced from 0.855 to 0.209. A simply feasible but less accurate absolute accuracy compensation method using tape measure on large distances was also tested, which resulted in similar scaling compensation compared to the surveying method or direct wand size compensation by a high precision 3D scanner. The presented validation methods can be less precise in some respects as compared to previous techniques, but they address an error type, which has not been and cannot be studied with the previous validation methods.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Absolute accuracy; Motion capture; Scale error; Validation; Wand-size optimization

Mesh:

Year:  2018        PMID: 29678420     DOI: 10.1016/j.jbiomech.2018.04.009

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  2 in total

1.  Accuracy of an electrogoniometer relative to optical motion tracking for quantifying wrist range of motion.

Authors:  Brian P McHugh; Amy M Morton; Bardiya Akhbari; Janine Molino; Joseph J Crisco
Journal:  J Med Eng Technol       Date:  2020-01-30

2.  Detection and Classification of Artifact Distortions in Optical Motion Capture Sequences.

Authors:  Przemysław Skurowski; Magdalena Pawlyta
Journal:  Sensors (Basel)       Date:  2022-05-27       Impact factor: 3.847

  2 in total

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