Author Topic: Gradual selection and optimization  (Read 16380 times)


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Gradual selection and optimization
« on: March 12, 2017, 12:32:57 PM »

I've seen a lot of topics on the subject, also some tutorials on the web, and i feel disappointed with the gradual selection and optimization steps, as each one contradicts the other one.

My workflow is a summary of what I've found, but not sure it's the best way :

After first alignement, I enter my GCP and activate all of them. Then I optimize cameras, leaving parameters by default.

From here:
1) Reconstruction Uncertainly - Level 10. I do it twice if necessary. Optimization
2) Reprojection Error - Level 0,5. Optimization
3) Number of images - 2. Optimization
4) Projection accuracy - 10% of total points. Optimization

Finally I chek the GCP errors and uncheck those I'm not satisfied with. And run one more optimization.

To your mind, it's a good way?

I'm also wondering if it's better to use all ot the parameters of the gradual selection or not? And if there is an order priority to use them?
And when launch optimization? After each step of gradual selection, or only one time at the end?
Also, is it better to use gradual selection with CGP (after one first optimization)?

Thanks for your help!

« Last Edit: March 12, 2017, 03:13:52 PM by Seboon »
Archaeologist - Topographer - Drone remote pilot


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Re: Gradual selection and optimization
« Reply #1 on: March 13, 2017, 11:39:38 AM »
I'm following pretty much the same workflow, with 180k / 120k alignment parameters


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Re: Gradual selection and optimization
« Reply #2 on: March 13, 2017, 05:00:37 PM »
I find that I use a similar workflow. Maybe one day we will see a guided process in which the software provides a series of steps and parameters to go through this in a more user-friendly fashion. I am happy with the software and have been glad to see it evolve over the years that I've been using it. Streamlining the optimization process will be huge step forward.


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Re: Gradual selection and optimization
« Reply #3 on: April 28, 2017, 11:06:47 AM »
OK, but Seboon doubt i think coluld be analyzing more deeply,
it's a crucial point to optimize cloud, in terms of next mesh generation and intrinsic accuracy, so i hope someone to add other consideration


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Re: Gradual selection and optimization
« Reply #4 on: May 08, 2017, 08:49:02 AM »
Still no official reply on this matter?

As stated by others I reckon some support regarding this process is highly desired. Considering its one of the most crucial ones with respect to the quality of the eventual model, I find it somewhat strange that there is not a comprehensive guide to it yet.