Motion Estimation of Articulated Objects from Perspective Views
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Modelling and estimating the pose of a human arm
Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
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In this paper, 3D articulated motion is recovered from image sequences by relying on a recursive smoothing framework. In conventional recursive filtering frameworks, the filter may misestimate the state due to degenerated observation. To cope with this problem, we take into account knowledge about the limitations of the state-space. Our novel estimation framework relies on the combination of a smoothing algorithm with a ``constraint-conscious'' enhanced Kalman filter. The technique is shown to be effective for the recovery of experimental 3D articulated motions, making it a good candidate for marker-less motion capture applications.