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However, DFD needs precise calibration of internal camera parameters.
Intrinsic camera parameters are gradually converged during vSLAM estimation process.
Most vSLAM algorithms assume known intrinsic camera parameters.
In the classic methods, the camera parameters are usually calculated and optimized by the reprojection error.
Iteration should be stopped if the optimized camera parameters meet the accuracy requirements.
However, they assumed that the internal camera parameters were known beforehand.
The size of the tomatoes is then measured from the obtained segmentation and camera parameters.
In turn, these modes optimize the camera parameters, based on extensive expert preference models.
The modification using the variable weight is reasonably effective in the absence of specific camera parameters.
Then, the size of the tomatoes is measured from the obtained segmentation and camera parameters.
The automatic estimation of camera parameters is also a future goal.
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