Closed AIBluefisher closed 9 months ago
The camera poses are camera to world. We use the same pose coordinate system as original NeRF repo: the local camera coordinate system of an image is defined in a way that the X axis points to the right, the Y axis upwards, and the Z axis backwards as seen from the image.
Thanks for your explanation. It would be better to make it clear on README.
I also have a question: for the aerial_street_fusion dataset, the camera poses in the aerial images seem not to share the same coordinate frame with the camera poses in the street images: I visualize the camera poses using COLMAP's GUI. As we can observe, the camera poses of the street images are higher than the aerial images. There must be a transformation to align the camera poses together. Or am I missing something?
Thanks for your explanation. It would be better to make it clear on README.
We write the coordinate system here https://github.com/city-super/MatrixCity?tab=readme-ov-file#data-download.
I also have a question: for the aerial_street_fusion dataset, the camera poses in the aerial images seem not to share the same coordinate frame with the camera poses in the street images: I visualize the camera poses using COLMAP's GUI. As we can observe, the camera poses of the street images are higher than the aerial images. There must be a transformation to align the camera poses together. Or am I missing something?
They are in the same coordinate system. Our coordinate system is not colmap system. So I think it is not reasonable to use the colmap GUI to visualize the camera poses. You can see the transforms_train.json. The height of street is 0.03 and the height of aerial is 2. The unit is 100m. You can read the explanation of our data structure https://github.com/city-super/MatrixCity?tab=readme-ov-file#data-structure.
Thanks for your explanation. It would be better to make it clear on README.
We write the coordinate system here https://github.com/city-super/MatrixCity?tab=readme-ov-file#data-download.
Thanks for you suggestion. We will open a new section to explain this thing to make it easier to notice
Thanks for your explanation. It would be better to make it clear on README.
We write the coordinate system here https://github.com/city-super/MatrixCity?tab=readme-ov-file#data-download.
Thanks for you suggestion. We will open a new section to explain this thing to make it easier to notice
We have updated the information here https://github.com/city-super/MatrixCity?tab=readme-ov-file#pose-file-structure.
Thanks for your explanation. It would be better to make it clear on README.
We write the coordinate system here https://github.com/city-super/MatrixCity?tab=readme-ov-file#data-download.
Thanks for you suggestion. We will open a new section to explain this thing to make it easier to notice
We have updated the information here https://github.com/city-super/MatrixCity?tab=readme-ov-file#pose-file-structure.
Thanks for your help and the quick update!
I also have a question: for the aerial_street_fusion dataset, the camera poses in the aerial images seem not to share the same coordinate frame with the camera poses in the street images: I visualize the camera poses using COLMAP's GUI. As we can observe, the camera poses of the street images are higher than the aerial images. There must be a transformation to align the camera poses together. Or am I missing something?
They are in the same coordinate system. Our coordinate system is not colmap system. So I think it is not reasonable to use the colmap GUI to visualize the camera poses. You can see the transforms_train.json. The height of street is 0.03 and the height of aerial is 2. The unit is 100m. You can read the explanation of our data structure https://github.com/city-super/MatrixCity?tab=readme-ov-file#data-structure.
Thanks for the confirmation. I converted the poses to COLMAP's format. There should be some other issues with my conversion code. I will try to fix it later.
Hi,
May I know the axis (e.g. down-right-backwards) and the direction (from camera to world or world to camera) of the camera poses?