Advances in Neural Information Processing Systems
The three-dimensional motion of humans is underdetermined when the observation 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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Howe, Nicholas; Leventon, Michael E.; and Freeman, William T., "Bayesian Reconstruction of 3D Human Motion from Single-Camera Video" (2000). Computer Science: Faculty Publications, Smith College, Northampton, MA.