Uncalibrated Camera confusion

Hi there,

I am trying to generate an orthomosaic of ten images, 6 of the images calibrate, but 4 end up in the uncalibrated images section. I tried the suggestion here by Marco to use a different Image Scale (1/2 or 1/4) and to use Geometrically Verified Matching, but this just makes me end up ALL images being classified as uncalibrated cameras.

Now, my dataset is problematic to begin with, as I flew oyster cages over calm water.

Now here are some pictures of my results after Initial Processing. I am confused as the 6 images that are calibrated have plenty of orange crosses, but the uncalibrated ones have no red crosses. Aren’t there supposed to be red crosses for me to try and manually calibrate with?

All ten of these images were flown with the same overlap (80% front, 70% side) height, drone, and camera. How is it it can find all the tie points between the six under these conditions but not the four?

Flown using a Phantom 4 Pro.


HI @snbitassetmanagement,

Manual calibration is a painful task, I would first try to get the best results by choosing the right processing options.
I understand that your data set will be quite difficult to calibrate as it contains a lot of water…
Sometimes setting the images scale on 2 could lead to more camera calibrated as it will increase the number of pixel processed by the software during step 1.
Geometrically Verified Matching is usually recommended for fields or flat terrain with many geometrical features. That’s why it did not help in your case.
Could you please share with us your data set?
And Quality Report (you can directly upload it in your reply)?
I would like to do some tests on my own and then I would let you know if I can get any better results.