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Bad Cameras

I recently conducted a survey of a heavy vegetated area. I had the app set to 85% overlap. A good portion of my cameras came in bad after processing the first step. I figured rather than attempting to  calibrate each camera I will try to re-run step 1 again. After it was completed it is still loaded with bad cameras.

I need to have camera in use for this survey as it is being used for something very important in regards to a new open pit area. 

Can you please suggest to me, what I should do in this instance?

I am using GCP’s, and have split the project into sub-projects.Still the same results. Do you have an updated explanation on how to manually calibrate cameras? The one on the support forum is very out dated and does not fully explain what to do when a camera has only a couple red crosses.

Any help will be appreciated.


Dear Jason,

Indeed, dense vegetation areas are more difficult to reconstruct due to the vase amount of leaves and branches that appear very different in different images.

In order to increase the number of uncalibrated images you can try to process step 1 with 1/2 keypoint image scale. This processing option can lead to higher number of calibrated images in case the default option (original keypoint image scale) does not calibrate all the images. 

You can find more information on how to improve the results for dense vegetation areas here:


Best regards,