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Confidence parameter #274
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Not quite. The alpha parameter for screening is defined by --pointWeight. In addition, it is possible that you have more confidence in some samples than others. (For example, if a point is facing the camera you are likely to be more confident than in a point viewed at a grazing angle). |
So, if I got it: There are some points |
Yes. Assuming that when you generated the point cloud you made the magnitudes of the normals of those points smaller. |
Amazing! But just a last question: how do I select those points? How does the code understand which points suffer the confidence? |
If the points have normals with magnitude 1, the associated weight will be 1 regardless of the confidence. So as long as you can scale the unit normals by the samples confidence (in the range [0,1])...
…On September 18, 2023 10:27:18 AM EDT, Clayes97 ***@***.***> wrote:
Amazing! But just a last question: how do I select those points? How does the code understand which points suffer the confidence?
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Hello, I am not understanding what the confidence parameter represents.
Should It be something related on how much I want to fulfill the constraint related to the screeming? Is therefore what is called alpha in the papers?
Thanks a lot for your answer
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