Bayesian Reconstruction of 3D Human Motion from Single-Camera Video

Authors

Nicholas Howe, Cornell UniversityFollow
Michael E. Leventon, Massachusetts Institute of Technology
William T. Freeman, Mitsubishi Electric Research Lab

Document Type

Article

Publication Date

2000

Publication Title

Advances in Neural Information Processing Systems

Abstract

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.

Volume

12

First Page

820

Last Page

826

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Rights

© the authors

Comments

Author’s submitted manuscript.

Recommended Citation

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.
https://scholarworks.smith.edu/csc_facpubs/106