Comments (1)
Hi,
did you have any chance to read how the level sigmas are initialized?
For instance, see the code and comments here:
https://github.com/luigifreda/pyslam/blob/master/feature_manager.py#L752
A sigma
represents the pixel dispersion we hit when localizing a feature at a considered octave/level.
Sigmas2
represent the corresponding variances.
Indeed, the information matrix is the inverse of the measurement covariance matrix and, in our case, we assume it to be diagonal.
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