Automated gap-filling for marker-based biomechanical motion capture data.

Abstract:

:Marker-based motion capture presents the problem of gaps, which are traditionally processed using motion capture software, requiring intensive manual input. We propose and study an automated method of gap-filling that uses inverse kinematics (IK) to close the loop of an iterative process to minimize error, while nearly eliminating user input. Comparing our method to manual gap-filling, we observe a 21% reduction in the worst-case gap-filling error (p < 0.05), and an 80% reduction in completion time (p < 0.01). Our contribution encompasses the release of an open-source repository of the method and interaction with OpenSim.

authors

Camargo J,Ramanathan A,Csomay-Shanklin N,Young A

doi

10.1080/10255842.2020.1789971

subject

Has Abstract

pub_date

2020-11-01 00:00:00

pages

1180-1189

issue

15

eissn

1025-5842

issn

1476-8259

journal_volume

23

pub_type

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