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Improving the inverse kinematics reconstruction of human movement from motion capture data
Author(s) -
Simonidis Christian,
Seemann Wolfgang
Publication year - 2010
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201010039
Subject(s) - kinematics , inverse kinematics , motion capture , acceleration , computer science , displacement (psychology) , motion (physics) , computer vision , inverse , work (physics) , artificial intelligence , mathematics , engineering , geometry , physics , classical mechanics , mechanical engineering , psychology , psychotherapist
Marker based motion capture methods are well known techniques for the acquisition of human motion. For the kinematic and dynamic analysis the recorded data is usually used to drive a rigid body model of the human body. Skin artifacts, which are caused by skin deformation and displacement of markers with respect to the underlying bone, are regarded as the most critical source of error in the inverse kinematics reconstruction of human movement. State‐of‐the‐art algorithms use optimization and multibody models with joint constraints in order to overcome these effects. This work presents an optimization based inverse kinematics approach, which is able to adapt the model kinematics subject‐specifically and to compute the time trajectories of kinematic variables from marker data including velocity and acceleration. (© 2010 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)