3 ms·

How feasible would it be to scale this up to several feet in diameter? Like if you wanted to scan furniture? The device itself by default looks to hold much sma

How feasible would it be to scale this up to several feet in diameter? Like if you wanted to scan furniture? The device itself by default looks to hold much smaller items.

_Microft 8mo ago
The dinosaur example lists an iPhone as source and none of their scanner models. It is also saying that it was recorded at a dinosaur theme park in Germany. This one might be meters long.
Symbiote 8mo ago
In that case I think you just take hundreds of photos by hand, probably with software which varies the focus as you take them so everything has a chance to be in focus. The device is a way to automake taking those ~300 photos (number from the marigold example).
thomas_OpenScan 8mo ago
scanning furniture is quite a challenge for photogrammetry. your best option would be NERF or Gaussian splatting and manually guiding the camera.
- digdugdirk 8mo ago
  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.
  - danielvaughn 8mo ago
    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 https://www.youtube.com/watch?v=YWaJEnKSM0w
  - thomas_OpenScan 8mo ago
    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/basics/ https://openscan-org.github.io/OpenScan-Doc/photogrammetry/b... and also the challenging surfaces lower on that site

How feasible would it be to scale this up to several feet in diameter? Like if you wanted to scan furniture? The device itself by default looks to hold much smaller items.

_Microft 8mo ago

The dinosaur example lists an iPhone as source and none of their scanner models. It is also saying that it was recorded at a dinosaur theme park in Germany. This one might be meters long.

Symbiote 8mo ago

In that case I think you just take hundreds of photos by hand, probably with software which varies the focus as you take them so everything has a chance to be in focus. The device is a way to automake taking those ~300 photos (number from the marigold example).

thomas_OpenScan 8mo ago

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

digdugdirk 8mo ago
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.
- danielvaughn 8mo ago
  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 https://www.youtube.com/watch?v=YWaJEnKSM0w
- thomas_OpenScan 8mo ago
  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/basics/ https://openscan-org.github.io/OpenScan-Doc/photogrammetry/b... and also the challenging surfaces lower on that site