[Work Log] Reconstruction problems

October 26, 2014

Visualizing 3d reconstruction of match candidates, and the results are problematic:

  1. No obvious good matches.
  2. Significant drift toward the camera.
  3. Marginal likelihood is promoting the worst reconstructions.

Issue 3 is possibly because there is a preference for placing structure near the camera center. If perturbation model is loose enough, each view can pull curves twoard its camera, and the likelihood reward is high.

How does it compare to simple triangulation?

Very poorly! The good triangulation candidates fit basically perfectly -- no perturbation necessary. We should reduce the perturbation variances, but this is causing the clique tree algorithm to become numerically unstable. Is there a better solution for piecewise reconstruction, that avoids taking inverse/cholesky of near-singular matrices?

Open questions

Actually, we have no real evidence that GP smoothing is even working. Need some unit tests:

Posted by Kyle Simek
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