Forum

Author Topic: Best strategy to scan thin objects on turn table  (Read 4528 times)

bmartin

  • Newbie
  • *
  • Posts: 15
    • View Profile
Best strategy to scan thin objects on turn table
« on: January 27, 2016, 10:20:33 PM »
Hello,

I want to assess if Agisoft is able to scan and reconstruct small thin objects on a turn table.  The kind of objects I have in mind is glasses (see the attached pictures for example).  I have down-sampled the posted image due to this forum size limitation but the real pictures are RAW of 5184x3456 pixels.  Also attached is a screenshot of the textured reconstructed (bad) model.

Details and questions:
1) I used my own pair of glasses for this fast test.  The real ones will NOT have their lenses mounted yet.  This will prevent some deformation near the part holding the lenses.  Knowing this, the reconstruction quality of the branches is what really interest me. If I can get it to work on this kind of structure, I'm pretty sure I will almost always work.
2) I put a piece of paper with text and graphics under the glasses hoping to help the software compute the alignment.  Is it a good idea?  Would it still work on a uniform white background given that the structure of interest shows close to no texture?
3) The angular rotation between the two attached images is representative of my image sequence (35 images in all).  Is it too much rotation?  Must the thin parts of the model show overlap or is my textured background enough for alignment?  What of the depth reconstruction? I seem to be getting very few "Tie points" along the glasses branches...

Thanks in advance for any advice...

Arie

  • Full Member
  • ***
  • Posts: 134
    • View Profile
Re: Best strategy to scan thin objects on turn table
« Reply #1 on: January 27, 2016, 11:19:53 PM »
The results you posted show clearly some limitations of photogrammetry. But with these type of objects I would guess even structured-light scanners would struggle (depending on the accuracy requirements and preparation work).
Two things that immediatly come to mind is the uniform surface color of the glasses frame and the shininess of the surface. Both individually are bad, combined even worse and I don't think you will be able to achieve any kind of good results.

My suggestion would be to coat the frame with some diffus reflecting substance (spray paint, for instance) and additionally trying to get some texture onto it (splashing some acrylic paint or similar).

For thin objects there has to be a fairly high amount of overlapping images, since the surface changes rapidly when only change the rotation slightly (especially in vertical direction). It is a good idea to have a well textured background as long as it stays in the same position relative to the glasses.

Also try optimizing the image-framing of the glasses, they should be covered by as many pixels as possible.

Good luck! Quite a challenging subject you have there.

James

  • Hero Member
  • *****
  • Posts: 754
    • View Profile
Re: Best strategy to scan thin objects on turn table
« Reply #2 on: January 28, 2016, 04:58:50 PM »
Another observation is that the paper is flapping around, and the paper clip isn't the most sturdy, so the glasses and paper may move independently of each other which would upset the alignment, but I appreciate this is just a test set up!

bmartin

  • Newbie
  • *
  • Posts: 15
    • View Profile
Re: Best strategy to scan thin objects on turn table
« Reply #3 on: January 29, 2016, 06:20:38 PM »
Thanks with your suggestions.
  • I tried the glasses again but very small angular displacement but the result was not better.
  • I tried also with brown plastic coffee stir sticks (one plain, another with spots of liquid paper to add features to it, see attachment). These sticks are a little wider than my glasses branches and much less specular. I get some mesh out of it but the result is still bad.

Maybe with a macro lense and taking pictures of something like 20mmx20mm all around the glasses I could get something but the acquisition process would not be suitable for mass usage. As Arie said, I think I reached the end of the photogrammetric approach.