Note of caution

This is the beta version of the dataset, and might change in the near future. We will keep registered users up-to-date, but please make sure to check this page for the latest version.

Update (2015/03/05)

Due to a bug in our code, some extrinsic camera matrices were incorrect. If you use the extrinsic camera matrices, please download the data again.

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What is in the archive?

This archive contains the beta version of the Sintel-depth training set. For each of the training sequences, it contains:

Depth maps & visualization

The depth maps contain the ground truth depth value (in meter) at each pixel. Additionally, we include a visualization showing the inverse depth.

Camera data

We provide the camera matrices (intrinsic and extrinsic) for the left camera.

SDK

The SDK includes example scripts to read/write the depth and camera data, and documentation on the data format.

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How was it generated?

The depth values are returned from Blender in an additional Z-buffer pass, similar to the optical flow.

The extrinsic camera matrix is given by Blender, as the world matrix of the camera object.

The intrinsic camera matrix is computed using the focal length as given by Blender, the hard-coded pixel dimensions of 32 px / mm, zero pixel skew, and the principal point at x = 511.5 and y = 217.5.

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Examples

These example show the final pass (top) and the corresponding depth data (bottom).

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Contact & citation

If you have any questions or problems regarding this dataset, please do not hesitate to contact us.

If you use this work, please cite:

@inproceedings{Butler:ECCV:2012,
title = {A naturalistic open source movie for optical flow evaluation},
author = {Butler, D. J. and Wulff, J. and Stanley, G. B. and Black, M. J.},
booktitle = {European Conf. on Computer Vision (ECCV)},
editor = {{A. Fitzgibbon et al. (Eds.)}},
publisher = {Springer-Verlag},
series = {Part IV, LNCS 7577},
month = oct,
pages = {611--625},
year = {2012}
}