Comments (4)
Basically, you can obtain camera-centered coordinates by applying the camera extrinsics.
Fitting to world coordinates can reduce the file size by the number of the camera, because there needs only one MANO parameter for each time step.
On the other hand, fitting to camera coordinates require MANO parameters for all views.
from interhand2.6m.
I have a question, a hand in different camera views has the same pose parameters except the first 3 global rotation parameters, am I right?
from interhand2.6m.
and it seems something wrong.. I just re-download the annotation file and run the updated render demo..
from interhand2.6m.
sorry there was a bug (confusion between meter and milimeter). Now, it works!
from interhand2.6m.
Related Issues (20)
- dataset version 0.0 HOT 2
- How to transform 3D joints set to MANO angle axis representation? HOT 6
- Background Images HOT 3
- Multiple black images in dataset/ Mismatch between annotation id and image id HOT 4
- 2.6m HOT 1
- Human3.6M
- rootnet_output
- Camera color calibration
- core dump
- Memory Leak in code HOT 3
- Problem in runiing
- can't open InterHand2.6M dataset HOT 1
- Some images are all black, is this normal? HOT 2
- Difference between 30fps and 5fps model HOT 4
- About 3D joints HOT 4
- can i obtain pre-trained model of rootNet about interHand2.6m dataset? HOT 1
- About mano shape HOT 2
- Hello, do you hance a smaller version of the InterHand dataset? HOT 4
- Two questions about hand keypoints detection HOT 3
- question regarding the intri and extri of the interhand2.6m dataset HOT 1
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