A Blind Source Separation Approach to Structure from Motion

  • Authors:

  • Jeff Fortuna;Aleix M. Martinez

  • Affiliations:

  • The Ohio State University, USA;The Ohio State University, USA

  • Venue:
  • 3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
  • Year:
  • 2006

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Abstract

We present an alternate approach to the problem of structure from motion (SfM) with noisy point measurements. With no information available about the joint density of three-dimensional points, the assumption of independence is the only reasonable one. With this assumption alone, the process of the factorization of the observed projections of inaccurately measured 3 dimensional points into motion and shape matrices is a blind source separation (demixing) problem in the presence of noise. This approach is very general, allowing the extension of all previous work on source separation to be applied to SfM in an information theory context. A significant reduction in the error of the estimation of the motion and shape matrices over other methods is possible.