Closed LareinaM closed 1 year ago
I think it's on their T-PAMI version section 6.2.2. Basically, it's just a normalizing factor between the pixel coordinates and the world coordinates.
I think it's on their T-PAMI version section 6.2.2. Basically, it's just a normalizing factor between the pixel coordinates and the world coordinates.
Hi @Walter0807, I read through that section, but it actually explains your DataReaderH36M
. I wonder how to obtain that factor, as it does not appear in any code scripts, thx!
I think it's on their T-PAMI version section 6.2.2. Basically, it's just a normalizing factor between the pixel coordinates and the world coordinates.
Hi @Walter0807, I read through that section, but it actually explains your
DataReaderH36M
. I wonder how to obtain that factor, as it does not appear in any code scripts, thx!
Sorry, it should be in Section 6.2.1 (LCN, T-PAMI 2020).
The 2.5d factor is the $\lambda$ here.
I think it's on their T-PAMI version section 6.2.2. Basically, it's just a normalizing factor between the pixel coordinates and the world coordinates.
Hi @Walter0807, I read through that section, but it actually explains your
DataReaderH36M
. I wonder how to obtain that factor, as it does not appear in any code scripts, thx!Sorry, it should be in Section 6.2.1 (LCN, T-PAMI 2020).
The 2.5d factor is the λ here.
Thanks for your reply! I wonder if there is any code related to this part, it's very hard to infer by oneself.
Sorry, I did not implement this part, the processed data was from LCN. If you have the original H36M data, you can estimate the corresponding $\lambda$ as described.
Sorry, I did not implement this part, the processed data was from LCN. If you have the original H36M data, you can estimate the corresponding λ as described.
Thanks for replying! From my understanding, in data processing script of lcn, joint_3d_image
is P_p
and joint_3d_camera
is P_c
, which should be root-centered and then used to calculate λ. When I tried using the above approach, the result is not the 2.5d_factor
.
Sorry, I did not implement this part, the processed data was from LCN. If you have the original H36M data, you can estimate the corresponding λ as described.
Thanks for replying! From my understanding, in data processing script of lcn,
joint_3d_image
isP_p
andjoint_3d_camera
isP_c
, which should be root-centered and then used to calculate λ. When I tried using the above approach, the result is not the2.5d_factor
.
Is the result close or not? I did not go into the code details of LCN, perhaps you can leave an issue there.
Sorry, I did not implement this part, the processed data was from LCN. If you have the original H36M data, you can estimate the corresponding λ as described.
Thanks for replying! From my understanding, in data processing script of lcn,
joint_3d_image
isP_p
andjoint_3d_camera
isP_c
, which should be root-centered and then used to calculate λ. When I tried using the above approach, the result is not the2.5d_factor
.Is the result close or not? I did not go into the code details of LCN, perhaps you can leave an issue there.
非常抱歉如此打扰了,我发现他们的repo从来不解答issue才到此处提问。如果按照上述的理解来minimize,λ会在0.2左右(实际上应该是4.6左右)。所以我以为是理解出现问题
Hi, sorry for the confusion. I consulted the LCN authors and here is the update:
我觉得可能是你算minimize的方式不太一样,可以看一下release版的实现看看是否有帮助。另外是否有可能是比例顺序不同,我注意到两个scale可能是倒数关系。
I think it's on their T-PAMI version section 6.2.2. Basically, it's just a normalizing factor between the pixel coordinates and the world coordinates.
Hi @Walter0807, I read through that section, but it actually explains your
DataReaderH36M
. I wonder how to obtain that factor, as it does not appear in any code scripts, thx!Sorry, it should be in Section 6.2.1 (LCN, T-PAMI 2020).
The 2.5d factor is the λ here.
My fault. λ (world to pixel) should be the reciprocal of 2.5d_factor
(pixel to world).
Thank you so much for your help! I figured it out now.
Hi, I looked through LCN and all data processing scripts, but none of them ever mentioned 2.5d-related fields. I wonder how is
2.5d_factor
in the pkl file is calculated?