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by totalview
620 days ago
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This is what happens to photogrammetry reconstruction around water and other areas where there are not enough camera angles seeing underneath the bridge to determine the 3-D geometry. This is usually rectified post processed by Google or someone serious about representing these bridges nicely. Often this is a 3-D modelers time, or if you are really enterprising, you can fly underneath the same bridge with a smaller drone and have the camera pointing up so that you can get really accurate photos underneath from which to do SfM/COLMAP. I wish this was solvable by GenAI, but the whole thing of garbage in garbage out really applies here. You don’t know what the structure is of that bridge looks like underneath the roadway unless you’ve taken multiple photos of it, and no two bridges are identical. I’m sure someone could train an AI on every bridge imaginable and we could get something better? |
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I have built systems that turned organic meshes into voxel and sparse voxel octree representations, modified them, and produced meshes of various parameters. It is doable, sometimes you just need to dig into the academic papers for a month or so.
Probably the team just has higher priority work. Building this post-processor for bridges seems doable by one engineer over a quarter. But the bridges being represented better than they are today won’t likely sell more copies of the flight simulator. So it’s probably very low priority to fix.