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Abstract:
Three-dimensional motion capture for human subjects is
underdetermined when the input is limited to a single camera, due
to the inherent 3D ambiguity of 2D video. We present a system that
reconstructs the 3D motion of human subjects from single-camera
video, relying on prior knowledge about human motion, learned from
training data, to resolve those ambiguities. After initialization
in 2D, the tracking and 3D reconstruction is automatic; we show
results for several video sequences. The results show the power of
treating 3D body tracking as an inference problem.
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