EricGuo5513
commented
8 months ago Hi, each dimension of the pose feature vector looks like this:
Recover global angle and positions for rotation data
root_rot_velocity (B, seq_len, 1)# root_linear_velocity (B, seq_len, 2)# root_y (B, seq_len, 1)# ric_data (B, seq_len, (joint_num - 1)3)# rot_data (B, seq_len, (joint_num - 1)6)# local_velocity (B, seq_len, joint_num*3)# foot contact (B, seq_len, 4)
On Tue, 31 Oct 2023 at 07:49, 1311894932 @.***> wrote:
the paper says pose is defined by root angular vec(Y), linear vec(XZ), root height. And LOCAL joints positions(R^3j), velocities(R^3j) and rotations(R^6j) in root space, finally there is binary features obtained by thresholding the heel and toe joint velocities to emphasize the foot ground contacts(R^4). So i think the dimensions of pose is 4(root)+21*12+4(binary features)=260? where is the lost 3 dimensions?
Any response will be appreciated!!!
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1311894932
the paper says pose is defined by root angular vec(Y), linear vec(XZ), root height. And LOCAL joints positions(R^3j), velocities(R^3j) and rotations(R^6j) in root space, finally there is binary features obtained by thresholding the heel and toe joint velocities to emphasize the foot ground contacts(R^4). So i think the dimensions of pose is 4(root)+21*12+4(binary features)=260? where is the lost 3 dimensions?
Any response will be appreciated!!!