Ok! I suspect that the software had some troubles finding matches in the area. Maybe the images look very similar, which could lead to having images that should not be together suggested for marking for the same MTP. In this case, it is better to only mark the images that really contain the feature you are interested in. If you do not mark the images that are 50m away, they will not be taken into account for the MTP. The pink circles show that the mark is an outlier.
Before following the next suggestions, please double check if there is enough overlap between the images in the problematic area. In addition, I would check if the quality of the images is as expected, e.g. sharp or blurry? Something you can check here, is how many matches were found in specific images. For this, you can select an image in the left sidebar of the rayCloud and check the orange crosses on the right as below:
If there are very few, it could explain why it is difficult to correctly calibrate them.
It seems as if you have flown a double grid mission (with a tilted camera) and that you have used the 3D Maps processing options template. These are the matching options in the 3D Maps template:
We can see that the time stamp of the images, image geolocation, image similarity and MTPs are taken into account for the computations. However, I believe that the “distance” option could help in your case, because it could improve the matches in the same area between the two grids. The first thing I would try, would be to run the 3D Model template, as shown below (notice the difference in the selected options):
If this did not work, I would suggest to uncheck the “Use capture time” checkbox and try again:
Let us know how this went
As usual, I would make a copy of the project to test this new suggestion, so that you can compare them.