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First of all, thank you for your contributions to this great library!
This question might or might not turn into a minor bug. I was reading the code for EvaluateRANSACBasedOnDistance and I found the following formula: result.inlier_rmse_ = error / std::sqrt((double)inlier_num);
However, error is collected by adding absolute values (as opposed to squared):
Given how the error is accumulated I was expecting to find a mean absolute error. Is there any reason for the denominator to be the square root of the sample size rather than just the sample size? I might be missing something (or maybe it is indeed a minor bug) so any ideas are welcome.
Thank you for your time :)
The text was updated successfully, but these errors were encountered:
Glad to be helpful! I'd be happy to do a PR with some guidance. Specifically, do you think the error should be squared during accumulation or averaged later by the number of samples? Also, is there a reference paper based on which this routine was implemented?
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branch).My Question
Hello everyone,
First of all, thank you for your contributions to this great library!
This question might or might not turn into a minor bug. I was reading the code for EvaluateRANSACBasedOnDistance and I found the following formula:
result.inlier_rmse_ = error / std::sqrt((double)inlier_num);
However,
error
is collected by adding absolute values (as opposed to squared):Given how the error is accumulated I was expecting to find a mean absolute error. Is there any reason for the denominator to be the square root of the sample size rather than just the sample size? I might be missing something (or maybe it is indeed a minor bug) so any ideas are welcome.
Thank you for your time :)
The text was updated successfully, but these errors were encountered: