3D Joints from Vertecies

[Daewon-Hwang]

Hello, I have one more question

I confirmed that VIBE extract 3D joints, vertecies, shapes, betas, etc.

But what I want is 3D joints in the original SMPL format (see link below).

https://khanhha.github.io/assets/images/smpl/joint_locations.png

Your model extract 49 3D Joints, but it looks different from the original SMPL Joint format.

Please advise how I can calculate 3D joints from vertices.

[mkocabas]

Hi @Daewon-Hwang,

To get SMPL joints you need the original J_regressor which you can find in SMPL pkl files.

Here is a small code snippet showing how to use it:

>>> import pickle as pkl

>>> smpl = pkl.load(open('SMPL_NEUTRAL.pkl', 'rb'), encoding='latin1')

>>> smpl.keys()     
                                                           
dict_keys(['J_regressor_prior', 'f', 'J_regressor', 'kintree_table', 'J',
 'weights_prior', 'weights', 'posedirs', 'pose_training_info', 'bs_style', 
'v_template', 'shapedirs', 'bs_type'])

>>> smpl['J_regressor'].shape # regressor for original 24 SMPL joints                                                                                                
(24, 6890)

>>> joints = smpl['J_regressor'] @ vertices # predicted vertices of shape (6890, 3)

[Daewon-Hwang]

Thank you very much for the answer.
I obtained a 3D joint as you indicated.
However, these joints are a root-relative joint.

Is there a way to get joints in a global position?

[mkocabas]

Is there a way to get joints in a global position?

Unfortunately, VIBE predicts root relative pose only.