Predicting Missing Marker Trajectories in Human Motion Data Using Marker Intercorrelations.

Abstract

Missing information in motion capture data caused by occlusion or detachment of markers is a common problem that is difficult to avoid entirely. The aim of this study was to develop and test an algorithm for reconstruction of corrupted marker trajectories in datasets representing human gait. The reconstruction was facilitated using information of marker… (More)
DOI: 10.1371/journal.pone.0152616

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@article{Glersen2016PredictingMM, title={Predicting Missing Marker Trajectories in Human Motion Data Using Marker Intercorrelations.}, author={\Oyvind Gl\oersen and Peter A Federolf}, journal={PloS one}, year={2016}, volume={11 3}, pages={e0152616} }