Juyong / Fast_RNRR

Source code for the paper "Quasi-Newton Solver for Robust Non-Rigid Registration" (CVPR2020 Oral).

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face registration result is very bad

ZHANG-SHI-CHANG opened this issue · comments

the result in face registration is very bad, like follow, 134 landmarks is used:
source:
image
target:
image
nricp result:
image
fast rnrr result:
image

Hi, how do you construct the correspondence between source and target models? If I understand correct, they have the same topologies. Besides, how do you set the weights?

Hi, how do you construct the correspondence between source and target models? If I understand correct, they have the same topologies. Besides, how do you set the weights?

yes, they have the same topologies, but i just use 134 landmarks, because i want to use it between different topologies. And i didn't modify the code about weights

Can you send the test models and the labeled landmarks to us via juyong@ustc.edu.cn?

Can you send the test models and the labeled landmarks to us via juyong@ustc.edu.cn?

👌,thx~

Hi, firstly, our method depends on geodesic calculation when sampling nodes, the geodesic code we used currently only supports closed mesh calculations, so maybe you need to fill holes first and then run it or change to a more suitable geodesic calculation method(in nodeSampler.cpp and geodesic.cpp). Secondly, the weights of regularization term and rotation term will greatly affect the results, you can adjust(decrease) them (paras.alpha and paras.beta in main.cpp) to make it more suitable for your models.

Hi, firstly, our method depends on geodesic calculation when sampling nodes, the geodesic code we used currently only supports closed mesh calculations, so maybe you need to fill holes first and then run it or change to a more suitable geodesic calculation method(in nodeSampler.cpp and geodesic.cpp). Secondly, the weights of regularization term and rotation term will greatly affect the results, you can adjust(decrease) them (paras.alpha and paras.beta in main.cpp) to make it more suitable for your models.

ok, i get it

Hi, firstly, our method depends on geodesic calculation when sampling nodes, the geodesic code we used currently only supports closed mesh calculations, so maybe you need to fill holes first and then run it or change to a more suitable geodesic calculation method(in nodeSampler.cpp and geodesic.cpp). Secondly, the weights of regularization term and rotation term will greatly affect the results, you can adjust(decrease) them (paras.alpha and paras.beta in main.cpp) to make it more suitable for your models.

ok, i get it

Hi, Mr Zhang,

Have you finally gotten good results on face registration?