Jun Liu wrote:
> Hi,
>
> I am using "FMatrixComputeRANSAC" in MVL (part of OXL) to compute fundamental
> matrix based on detected feature points correspondences. There is very weird
> output though: given exactly the same input data, it will produce different
> fundamental matrix every time! The matrices differs from each other
> significantly and there is also difference in number of inliers/outliers!
>
> Is this a bug? Any one who could provide any suggestion on robust computation
> of fundamental matrix is very much appreciated.
>
> Regards,
> Jun
I haven't used this particular code, but here are my observations based
on another implementation of the algorithm: RANSAC takes random samples
of the minimum number of feature point correspondences necessary to
compute the fundamental matrix, and computes how many of the entire set
of correspondences are consistent with that matrix (the socalled
"inliers"). The number of iterations (trials) to be run is continually
updated, based on the the number of trials so far, the maximum number of
inliers found, total sample size, and the userspecified confidence of
the solution's correctness. Because the sampling is random, the number
of trails and best solution found will vary from run to run.
You could try increasing the confidence threshold to choose more
samples, or, if consistency is important, set the random number
generator seed before each run. If only a small fraction of the
correspondences that you feed the algorithm are correct, RANSAC may have
a hard time to find the correct solution, perhaps due in part to
epipolar matching ambiguity.
Harry Voorhees
_________________________________________________________
Harry L. Voorhees, hlv@..., 9784755279
Stellar Science Ltd. Co., http://www.stellarscience.com
"Stellar Scientific Software Solutions"
