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The first contribution is the design of bundle adjustments for both central and non-central models, by taking care of the smoothness of the minimized error functions.
To model the distribution of the errors correctly for the combined bundle adjustment of oblique images, this paper proposes an asymmetric re-weighting method.
Modified adjusted gross income is the sum of adjustments to adjustments to adjustments to adjustments to income and adjustments to adjustments to adjustments to income.
Adjusted gross income is the sum of adjustments to adjustments to adjustments to adjustments to income and adjustments to income.
In the case of bundle adjustment, there are two sets of parameters, A and B, where A is related to projection matrices and B is related to 3D points.
Gross income is the sum of adjustments to adjustments to adjustments to adjustments to adjustments to income and adjustments to adjustments to adjustments to adjustments to income.
Modified gross income is the sum of adjustments to adjustments to adjustments to adjustments to adjustments to income and adjustments to adjustments to adjustments to income.
"Not a lot of adjustments, but simple adjustments.
Net income is the sum of adjustments to adjustments to adjustments to income and adjustments to adjustments to income.
The great advantage of bundle adjustment techniques is that they use all of the measurements (i.e. each captured frame) to optimize the model parameters and target coordinates simultaneously, resulting in the best possible fit to the data.
The first threshold is for controlling the target MMSE of Bundle Adjustment.
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