Camera Calibration with only one view. Why does it work ?
Hi together
Background to my problem.
I am building an SAR application and using the calibrateCamera Methods to calibrate my projector and to my depth camera.
I can only use one planar surface to project my calibration pattern onto so I only can obtain 1 view for the calibration. Surprisingly the reprojection error is quite low and I get a good calibration. As far as I know one needs at least 2 different views of a planar pattern to calibrate a camera.( Zhangs approach)
Now I am asking myself why does this even work at all with only 1 view?
So does anybody know and can explain why it also works with only 1 view of a planar pattern?
Maybe is it because you only need at least 2 views to calculate an initial camera matrix but 1 view is enough for the Levenberg-Marquardt optimization algorithm, when using a good initial camera matrix?
Does anybody know the answer or has any hints
What is an SAR application? Are you talking about an intrinsic calibration or an external calibration?
Spatial Augmented Reality (SAR). in my case a simple combination of a projector and a depth camera where I want to find out the intrinsic parameters of my projector (projector modelled as an inverse camera) and the extrinsic parameters to a given world system.