Sandau, Martin3; Koblauch, Henrik3; Moeslund, Thomas B.4; Aanæs, Henrik1; Alkjær, Tine3; Simonsen, Erik B.5
1 Department of Applied Mathematics and Computer Science, Technical University of Denmark2 Image Analysis & Computer Graphics, Department of Applied Mathematics and Computer Science, Technical University of Denmark3 University of Copenhagen4 Aalborg University5 Department of Electrical Engineering, Technical University of Denmark
Estimating 3D joint rotations in the lower extremities accurately and reliably remains unresolved in markerless motion capture, despite extensive studies in the past decades. The main problems have been ascribed to the limited accuracy of the 3D reconstructions. Accordingly, the purpose of the present study was to develop a new approach based on highly detailed 3D reconstructions in combination with a translational and rotational unconstrained articulated model. The highly detailed 3D reconstructions were synthesized from an eight camera setup using a stereo vision approach. The subject specific articulated model was generated with three rotational and three translational degrees of freedom for each limb segment and without any constraints to the range of motion. This approach was tested on 3D gait analysis and compared to a marker based method. The experiment included ten healthy subjects in whom hip, knee and ankle joint were analysed. Flexion/extension angles as well as hip abduction/adduction closely resembled those obtained from the marker based system. However, the internal/external rotations, knee abduction/adduction and ankle inversion/eversion were less reliable.
Medical Engineering and Physics, 2014, Vol 36, Issue 9, p. 1168-1175
bevægelse; Markerless; Motion capture; Tracking; Gait analysis; Biomechanics; 3D reconstruction; Dense point cloud; Stereo vision; Photogrammetry; Iterative closest point; Articulated model