Quantitative depth recovery from time-varying optical flow in a Kalman filter framework

Authors:
John Barron;Wang Kay Jacky Ngai;Hagen Spies
Affiliations:
Department of Computer Science, University of Western Ontario, London, Ontario, Canada;Department of Computer Science, University of Western Ontario, London, Ontario, Canada;ICG-III: Phytosphere, Research Center Jülich, Jülich, Germany
Venue:
Proceedings of the 11th international conference on Theoretical foundations of computer vision
Year:
2002

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Abstract

We present a Kalman filter framework for recovering depth from the time-varying optical flow fields generated by a camera translating over a scene by a known amount. Synthetic data made from ray traced cubical, cylinderal and spherical primitives are used in the optical flow calculation and allow a quantitative error analysis of the recovered depth.