Motion, independent of forces, is described by kinematic parameters (usually using Denavit-Hartenberg convention)
that have been used widely in biomechanical fields. Examples of these fields include robotics, human
motion studies, and biomechanical structures' design and control; e. g. for exoskeleton and artificial human
arm. A common way to precisely measure the joints movements is by using a motion capture system. Until
now, the most successful motion capture technology is optical motion capture; this is due to its highly accurate
measurement of small reflective markers that are attached to some relevant body landmarks.
This paper addresses the problem of estimating the human arm kinematics parameters from video or captured
images of human arms. We introduce a new robust framework that leads to reliable and accurate estimation of
shoulder and elbow center of rotations along with the arm kinematics parameters.
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