Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

3D ground truth interpretation #13

Open
teasherm opened this issue Aug 15, 2018 · 2 comments
Open

3D ground truth interpretation #13

teasherm opened this issue Aug 15, 2018 · 2 comments

Comments

@teasherm
Copy link

Hello,

First, thank you for sharing this great work. A quick question about the panoContext_box_train.t7 tensor:

The paper mentions 6 ground truth 3D parameters: sw, sl, sh, tx, tz, r_theta. The first 6 elements in the box tensor above (box[{{1}{1}{1,6}}]), which I believe contain those parameters for the first example image, read:

sw = -0.5154072972870558
sl = -0.6748731674025037
sh = -1.316387492900166
tx = -0.24216556285261603
tz = -0.2114205765327388
r_theta = 0.08283438070600802

A naive interpretation would suggest that the room is almost 3x higher than it is wide? Is there a reason for the negative scale factors? Any guidance on interpretation would be much appreciated

@zouchuhang
Copy link
Owner

@teasherm The box parameter stored in "panoContext_box_train.t7" are normalized to be zero mean and standard deviation, causing those negative scale factors. I include the preprocessing script in "preprocessPano.m", you can refer to L94-239 for computing the box parameters.

@teasherm
Copy link
Author

Ah, I see. Thanks @zouchuhang !

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants