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Explanation of the optimization equation #48

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JinraeKim opened this issue Aug 3, 2022 · 2 comments
Open

Explanation of the optimization equation #48

JinraeKim opened this issue Aug 3, 2022 · 2 comments

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@JinraeKim
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In this paper,
I cannot guess the meaning of variables in Eq. (1).

I guess E_D is at least the sum of squares of depth errors.
What is v(p, q)? How can we pick p and q from image N for E_N and E_S?
What is T_{obs} in E_D?

Please give me an explanation with an example.

@JinraeKim
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Also, how did you approximate the equation? There is a reference paper but the notations are different and looks not enough to guess the approximation

@jiayily
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jiayily commented Sep 12, 2024

1.T_{obs} is the observed pixels, that is pixels with depth data from both the raw sensor and the rendered mesh.
2.p is a neighbor of q in surface normal image.
3.This vector is used to guarantee consistency between surface normal with predicted depth given p and q is in on the same surface.

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