Dataset Open Access
Fischer, Tobias;
Chang, Hyung Jin;
Demiris, Yiannis
License + Attribution
This dataset is licensed under CC BY-NC-SA 4.0. Commercial usage is not permitted. If you use this dataset or the code in a scientific publication, please cite the following paper:
@inproceedings{FischerECCV2018,
author = {Tobias Fischer and Hyung Jin Chang and Yiannis Demiris},
title = "{RT-GENE: Real-Time Eye Gaze Estimation in Natural Environments}",
booktitle = {European Conference on Computer Vision},
year = {2018},
month = {September},
pages = {339--357}
}
This work was supported in part by the Samsung Global Research Outreach program, and in part by the EU Horizon 2020 Project PAL (643783-RIA).
More information can be found on the Personal Robotic Lab's website: https://www.imperial.ac.uk/personal-robotics/software/.
Overview
The dataset consists of two parts: 1) One where the eyetracking glasses were worn (and thus ground truth labels for head-pose and eye gaze are available; suffix _glasses), and 2) One with natural appearances (no eyetracking glasses are worn; suffix _noglasses). The _noglasses images were used to train subject-specific GANs, and these GANs were used to inpaint the region covered by the eyetracking glasses in the _glasses images.
There is code accompanying this dataset: https://github.com/Tobias-Fischer/rt_gene. Please use the issue tracker in the code respository if you have questions regarding the dataset.
Subjects / 3-Fold evaluation
15 participants were recorded in 17 sessions. Session 014 is a second recording of participant 002, and session 015 is a second recording of participant 005 (different days and different camera poses were used).
We used a 3-fold evaluation, with the three folds consisting of the following sessions (test on one of the groups, training with the remaining two groups):
The validation set consists of sessions 's014', 's015' and 's016'.
While the MATLAB script (prepare_dataset.m; see code repository) creates train and test images for each subject, all images were used for the evaluation (see evaluate_model.py).
Labeled dataset (sXYZ_glasses)
The file for each subject contains the following information:
Unlabeled dataset (sXYZ_noglasses)
Name | Size | |
---|---|---|
LICENSE.txt
md5:7931e7a7beaa761140368e83f55181c2 |
16.7 kB | Download |
s000_glasses.tar
md5:5133796344086cab7421adb87a067cd4 |
2.0 GB | Download |
s000_noglasses.tar
md5:66a1bef70557a794e82a999928e9df3f |
798.5 MB | Download |
s001_glasses.tar
md5:003443f333e0f3313213c49d0b87d4d9 |
4.0 GB | Download |
s001_noglasses.tar
md5:fb79a8d6e2f87e7262dcacfeb8c450bd |
590.4 MB | Download |
s002_glasses.tar
md5:049edf16f5912c393b9a40b46eca2ad6 |
2.0 GB | Download |
s002_noglasses.tar
md5:b16ee2b7c18d773a274a58b0cd8993cd |
596.3 MB | Download |
s003_glasses.tar
md5:58c50ec9d3fbb893c677c154062aff0b |
4.4 GB | Download |
s003_noglasses.tar
md5:a7903b887f139461d1bd349ad90264e0 |
225.7 MB | Download |
s004_glasses.tar
md5:01cb190e984cf97b78993bd3cf028ace |
1.8 GB | Download |
s004_noglasses.tar
md5:f046a5316b6db55d567bf7b8c937ab61 |
298.6 MB | Download |
s005_glasses.tar
md5:49f8ca811b3485fa141346856f860633 |
654.8 MB | Download |
s005_noglasses.tar
md5:fc84b337f90c71083c8ee9e93af978b0 |
344.9 MB | Download |
s006_glasses.tar
md5:2c1fd43bf7069c2b0cd2540ba0c3fde9 |
2.6 GB | Download |
s006_noglasses.tar
md5:98147f7db20f14080bf319f42a7e5698 |
472.2 MB | Download |
s007_glasses.tar
md5:52935565e781b25225e085f572fd4e8d |
2.0 GB | Download |
s007_noglasses.tar
md5:5f1d86f8ec152b1334d3812a686f02c7 |
122.2 MB | Download |
s008_glasses.tar
md5:48298971c9a80f5112bcbf7247c724b0 |
1.9 GB | Download |
s008_noglasses.tar
md5:ef870a89441bc3498bea6765840cbce2 |
417.2 MB | Download |
s009_glasses.tar
md5:518ecc5d2045581c96a055157a047132 |
1.3 GB | Download |
s009_noglasses.tar
md5:77bfc049a55fbef60b4758298b1e6e1c |
264.2 MB | Download |
s010_glasses.tar
md5:e0aee15af925bd604229a5d6f75e313b |
3.8 GB | Download |
s010_noglasses.tar
md5:755a33f6d9d6d06ab15e5aa725030de9 |
1.2 GB | Download |
s011_glasses.tar
md5:970002164be3b55204756059bb87efaa |
3.2 GB | Download |
s011_noglasses.tar
md5:a44edb49bff0b84fc44e6896e8586e90 |
891.8 MB | Download |
s012_glasses.tar
md5:106bccc117f4664383916420cd594303 |
437.4 MB | Download |
s012_noglasses.tar
md5:7367837c1f3c6047d24f020c79b1aa8f |
217.5 MB | Download |
s013_glasses.tar
md5:b5fbcf8c8513f7781988ba01e9209e81 |
3.8 GB | Download |
s013_noglasses.tar
md5:5bcc872060612c7435b575f1838f6f05 |
606.0 MB | Download |
s014_glasses.tar
md5:00c87ff4e83d7080f13cdedecd7f86d4 |
2.3 GB | Download |
s014_noglasses.tar
md5:95442bc63f2575a70a861bce3834b88d |
360.4 MB | Download |
s015_glasses.tar
md5:2ea51833a1a3b5b422908a09316367b8 |
1.6 GB | Download |
s015_noglasses.tar
md5:1a96d411ad297cdbe802e7ac992d3a90 |
137.8 MB | Download |
s016_glasses.tar
md5:7a3ea57f066904e98c4ee3c3a1032eaa |
2.0 GB | Download |
s016_noglasses.tar
md5:8b50676c9b297539cc9e57acb04f42e3 |
310.7 MB | Download |
Views | 3,195 |
Downloads | 32,154 |
Data volume | 70.0 TB |
Unique views | 2,850 |
Unique downloads | 3,752 |