How to normalize uint16 depth image for training?

vision
1

The depth image rendered from the ScanNet dataset is in uint16, after dividing the depth by the shift (1000), the depth values are in the range of [0, 1 < some positive float < 10], how to normalize the depth to [0, 1] (per dataset) for training?

2

So the question is whether you want per-dataset or per-image normalization - I would imagine that you want global because depth is a physical quantity (but in medical imaging it is not uncommon to use per-image, in particular when working with images taken by different scanners). If you need global, you’d need to iterate over the dataset once during preprocessing and find the maximum.

Best regards

Thomas

3

I need the per-dataset normalization. By saying iterate over the dataset and find the maximum, do you mean over the training set? or including the test set?

4

The rules are that you should use the training set.
The next question then is what to do when the test set a larger depth somewhere. I’d probably just clamp it down to 1. In a good training set, I would expect the training set to max out the depth reported by the camera somewhere.

Best regards

Thomas

5

Thanks, Tom. So then I can normalize the depth by using (depth - min_depth) / (max_depth - min_depth) where max_depth is the maximum depth value over the whole training set, right?

6

That’s what I’d do, though maybe you might just keep min_depth 0 or so.

7

I have a question regarding normalising depth images. How did you find the maximum depth value over the whole training set?