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Comment by thomas_OpenScan | Hacker News Reader

scanning furniture is quite a challenge for photogrammetry. your best option would be NERF or Gaussian splatting and manually guiding the camera.

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Can you please explain a bit more about why it's a difficult photogrammetry challenge, or point me in the direction of resources so I can learn more about it myself? This is an exact project on my projects list, so I'd love to have a better grounding in the topic when I get around to diving in to it.

Edit: I'm more focused on getting a dimensionally accurate/stable model, vs an esthetically pleasing one, if that matters. The hope is to be able to scan a broken chair and be able to design a jig in CAD that I could then 3d print for holding a specific piece in place while everything goes back together.

Same, which is why I asked. My naive intuition is that if you had an industrial grade turntable, like the one in the below video, you could hack together a hardware setup.

https://www.youtube.com/watch?v=YWaJEnKSM0w

Most recent gaussian and nerf to mesh algorithms are surprisingly good at getting reasonable results for objects that traditional photogrammetry would struggle with. The main challenge are reflective and uniform surfaces (e.g. lether or coated wood). See this overview what you'd want for perfect photogrammetry: https://openscan-org.github.io/OpenScan-Doc/photogrammetry/b... and also the challenging surfaces lower on that site

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