There is a way to adjust the rays bundles just from GCPs?

ODM
#1

Hi to all,

I’m trying to create a model from non-georeferenced photos (all metadata removed).
I have a set of measured GCPs in a local coordinates system and want to use them to derive all the parameters of the aero-triangulation process, so the photos can be undirstorted and the model can be adjusted with them.
I assigned a random UTM reference to my GCPs coordinates just because a georeference is needed for them.

Without any additional parameter I sent the task to a dockerized ODM machine.

As the photos are not georeferenced, it seems to me that the GCPs were not taken into account, because the computed internal parameters of the shots differ a lot from the original ones, and the model is not adjusted or geo-spatially located on the GCPs.

I work sometimes with non-georeferenced local coordinates systems. There is a way to adjust the rays bundles just from GCPs?

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#2

Welcome! Thanks for helping me make the geohash algorithm for QGIS! Great to see you in our community :sunglasses:

This is all quite above me, so hopefully Piero and/or Stephen can comment soon to help you.

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#3

Hi Saijin, thank you, I’m testing ODM and I think it is a powerful tool.

My problem seems to be the name and/or location of the gcp_list.txt file. I was confused about where it must be.

If somene is interested, we can remove the images metadata and process the model just with GCPs. I added 500000 m to the mapX and 100000 m to the mapY coordinates and started the gcps file with an EPSG:32631 line. The model was well adjusted and georeferenced near the null island. It is easy to remove the reference and move it to original local system later.

I am now testing its accuracy versus the non-removed metadata images dataset.

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#4

Ah good. I was going to suggest there’s a likely bug otherwise, but it sounds like it works as expected.

It’ll be interesting to see what it does with the exif in there: I don’t expect that will turn out well: the extrinsic will have some conflicts. If your lucky, it will prioritize the info from the GCPs, but I’m not sure. It will interesting to see for sure.

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#5

I’d raise the possibility of a bug Don't use invalid triangulated points · mapillary/OpenSfM@07a3c2f · GitHub

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#6

Thank you all. The process run out of memory in the mesh step. The dense cloud point was created but real objects or structures have a big inclination respect the general slope’s normal. Also, some area wasn’t covered, maybe recognized as outliers. I need to review the logs.
I think that we need to transform local to global GCPs coordinates, or process images without exif georeference metadata if working in a (non-georeferenced) local reference system.

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