Multi-constrained inverse kinematics for the human hand.
Measuring the spatial and temporal characteristics of hand movement is a challenging task due to the large number of degrees of freedom (DOF) in the hand. This paper presents a multi-constrained inverse kinematics (IK) approach for hand motion estimation from motion capture data. The IK approach satisfies a set of prioritized motion and postural constraints for each hand joint and link. The high-priority constraint is fully satisfied, while the fulfillment of the low-priority constraints is achieved as long as no conflict with the high-priority constraint exists. The proposed approach can aid marker-based motion capture technologies in accurately reconstructing discontinuities or erroneous marker trajectory segments resulting from occluded, missing, or flipped markers. The performance of the multi-constrained IK approach for the hand is tested for a full range of continuous hand motion.
Electrical and Computer Engineering Department, University of Waterloo, Waterloo ON N2L 3G1, Canada. asamadani@uwaterloo.ca
Ali-Akbar
AA
Samadani
Dana
D
Kulić
Rob
R
Gorbet
D000465:Algorithms; D001696:Biomechanical Phenomena; D006225:Hand / Q000033:anatomy & histology* / Q000502:physiology*; D006801:Humans; D007596:Joints; D008953:Models, Anatomic; D015233:Models, Statistical; D009068:Movement; D015203:Reproducibility of Results; D013997:Time Factors