Dataset Open Access

RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments

Cortacero, Kevin; Fischer, Tobias; Demiris, Yiannis

The RT-BENE dataset is licensed under CC BY-NC-SA 4.0. Commercial usage is not permitted. If you use our blink estimation code or dataset, please cite the relevant paper:

@inproceedings{CortaceroICCV2019W,
author={Kevin Cortacero and Tobias Fischer and Yiannis Demiris},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision Workshops},
title = {RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments},
year = {2019},
}

More information can be found on the Personal Robotic Lab's website: https://www.imperial.ac.uk/personal-robotics/software/.

Overview

We manually annotated images that are contained in the "noglasses" part of the RT-GENE dataset with blink annotations. This dataset contains the extracted eye image patches and associated annotations.

In particular, rt_bene_subjects.csv is an overview CSV file with the following columns:

  1. id
  2. subject csv file
  3. path to left eye images
  4. path to right eye images
  5. training/validation/discarded category
  6. fold-id for the 3-fold evaluation.

Each individual "blink_labels" CSV file (s000_blink_labels.csv to s016_blink_labels.csv) contains two columns:

  1. image file name
  2. label, where 0.0 is the annotation for open eyes, 1.0 for blinks and 0.5 for annotator disagreement (these images are discarded)

Associated code

Please see the code repository for code allowing to train and evaluate a deep neural network based on the RT-BENE dataset. The code repository also links to pre-trained models and code for real-time inference.

We thank the Personal Robotics Lab members at Imperial College for their support during this research. This work was supported by the European Union H2020 Framework Programme (Project PAL, H2020-PHC-643783), and a Royal Academy of Engineering Chair in Emerging Technologies.
Files (937.0 MB)
Name Size
rt_bene_subjects.csv
md5:a07810daaf6d2053a9ed1f782e5f360c
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s000_blink_labels.csv
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s000_noglasses_eyes.tar
md5:9c4591dd8eb1c6dced120f768c8acd23
98.9 MB Download
s001_blink_labels.csv
md5:e643663fe17a7def64b616b06be992ec
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s001_noglasses_eyes.tar
md5:63784833a779e48a670d183b387cc501
72.4 MB Download
s002_blink_labels.csv
md5:df2566fc9218ab81036342ce04d7f2f0
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s002_noglasses_eyes.tar
md5:4ae9f7dbd3ec23b9997bbbfa54e05f2b
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s003_blink_labels.csv
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s003_noglasses_eyes.tar
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s004_blink_labels.csv
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s004_noglasses_eyes.tar
md5:9a31825d3446a3b25cf23160ec46be7a
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s005_blink_labels.csv
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s005_noglasses_eyes.tar
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s006_blink_labels.csv
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s006_noglasses_eyes.tar
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s007_blink_labels.csv
md5:1b62a3a2c45efbd0af3ef36900151ead
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s007_noglasses_eyes.tar
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s008_blink_labels.csv
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s008_noglasses_eyes.tar
md5:91da9e6da1075e80f60307516055ee6c
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s009_blink_labels.csv
md5:c740478ed59c9c5cf5e34144ab3ed272
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s009_noglasses_eyes.tar
md5:7aad909fc39baaa4cbc53051d7d6c89f
31.8 MB Download
s010_blink_labels.csv
md5:4f89f810193adf22ec9f990a05d42bea
423.6 kB Download
s010_noglasses_eyes.tar
md5:c17f5ce5316cc74356ec09b17b46faac
140.0 MB Download
s011_blink_labels.csv
md5:f1159a7dd8d80880074cd609b0b33cc7
329.2 kB Download
s011_noglasses_eyes.tar
md5:9a9295e571d803e138f9094a6f0331a3
114.2 MB Download
s012_blink_labels.csv
md5:7722524624f3dcf53116e7081a7de5c7
31.8 kB Download
s012_noglasses_eyes.tar
md5:e925025262025b3c6145c42b08255ba1
9.9 MB Download
s013_blink_labels.csv
md5:e220c8bccdf1b6c5a3886bfdb30a9d1f
255.7 kB Download
s013_noglasses_eyes.tar
md5:ad46bc84d80a35c57d36921f411cb5df
75.3 MB Download
s014_blink_labels.csv
md5:7b3d85a970e90ca4627f2cac39d3a1e6
137.8 kB Download
s014_noglasses_eyes.tar
md5:68c8282b56afa29fad7cfb50deb7b9cc
41.1 MB Download
s015_blink_labels.csv
md5:825af2e4609c3f1534438777fbf7c45e
55.4 kB Download
s015_noglasses_eyes.tar
md5:cc2547496bb28ed5298f11c587b67fc6
16.5 MB Download
s016_blink_labels.csv
md5:c449b5da2fee9ecc1c8cbb0f15d179f3
116.5 kB Download
s016_noglasses_eyes.tar
md5:d64f7e91f234ab3ac3ddbf19bbef427a
36.7 MB Download
  • K. Cortacero, T. Fischer and Y. Demiris. "RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments", ICCV 2019 Workshop on Gaze Estimation and Prediction in the Wild

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