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------------
status: published
title: HELEN
desc: HELEN is a dataset of face images from Flickr used for training facial component localization algorithms
subdesc: HELEN includes 2,330 images from Flickr found by keyword searches for "portrait", "wedding", "outdoor", "boy", "studio", and "family"
caption: Selected images from the HELEN dataset
slug: helen
cssclass: dataset
caption: Example images from the HELEN dataset
image: assets/background.jpg
published: 2019-9-23
updated: 2019-9-23
authors: Adam Harvey
------------
# HELEN Dataset
### sidebar
### end sidebar
Helen is a dataset of annotated face images used for facial component localization. It includes 2,330 images from Flickr found by searching for "portrait" combined with terms such as "family", "wedding", "boy", "outdoor", and "studio".[^orig_paper]
The dataset was published in 2012 with the primary motivation listed as facilitating "high quality editing of portraits". However, the paper's introduction also mentions that facial feature localization "is an essential component for face recognition, tracking and expression analysis."[^orig_paper]
Irregardless of the authors' primary motivations, the HELEN dataset has become one of the most widely used datasets for training facial landmark algorithms, which are essential parts of most facial recogntion processing systems. Facial landmarking are used to isolate facial features such as the eyes, nose, jawline, and mouth in order to align faces to match a templated pose.
This analysis shows that since its initial publication in 2012, the HELEN dataset has been used in over 200 research projects related to facial recognition with the vast majority of research taking place in China.
Commercial use includes IBM, NVIDIA, NEC, Microsoft Research Asia, Google, Megvii, Microsoft, Intel, Daimler, Tencent, Baidu, Adobe, Facebook
Military and Defense Usage includes NUDT
http://eccv2012.unifi.it/
TODO
- add proof of use in dlib and openface
- add proof of use in commercial use of dlib? ibm dif
- make landmark over blurred images
- add 6x6 gride for landmarks
- highlight key findings
- highlight key commercial usage
- look for most interesting research papers to provide example of how it's used for face recognition
- estimated time: 6 hours
- add data to github repo?
| Organization | Paper | Link | Year | Used Duke MTMC |
|---|---|---|---|
| SenseTime, Amazon | [Look at Boundary: A Boundary-Aware Face Alignment Algorithm](https://arxiv.org/pdf/1805.10483.pdf)
| 2018 | year | ✔ |
| SenseTime | [ReenactGAN: Learning to Reenact Faces via Boundary Transfer](https://arxiv.org/pdf/1807.11079.pdf) | 2018 | year | ✔ |
The dataset was used for training the OpenFace software "we used the HELEN and LFPW training subsets for training and the rest for testing" https://github.com/TadasBaltrusaitis/OpenFace/wiki/Datasets
The popular dlib facial landmark detector was trained using HELEN
In addition to the 200+ verified citations, the HELEN dataset was used for
- https://github.com/memoiry/face-alignment
- http://www.dsp.toronto.edu/projects/face_analysis/
It's been converted into new datasets including
- https://github.com/JPlin/Relabeled-HELEN-Dataset
- https://www.kaggle.com/kmader/helen-eye-dataset
The original site
- http://www.ifp.illinois.edu/~vuongle2/helen/
### Example Images
{% include 'dashboard.html' %}
{% include 'supplementary_header.html' %}
### Age and Gender Distribution
{% include 'age_gender_disclaimer.html' %}
=== columns 2
```
single_pie_chart /datasets/helen/assets/age.csv
Caption: HELEN dataset age distribution
Top: 10
OtherLabel: Other
```
```
single_pie_chart /datasets/helen/assets/gender.csv
Caption: HELEN dataset gender distribution
Top: 10
OtherLabel: Other
```
=== end columns
{% include 'cite_our_work.html' %}
#### Cite the Original Author's Work
If you find the HELEN dataset useful or reference it in your work, please cite the author's original work as:
<pre>
@inproceedings{Le2012InteractiveFF,
title={Interactive Facial Feature Localization},
author={Vuong Le and Jonathan Brandt and Zhe L. Lin and Lubomir D. Bourdev and Thomas S. Huang},
booktitle={ECCV},
year={2012}
}
</pre>
### Footnotes
[^orig_paper]: Le, Vuong et al. “Interactive Facial Feature Localization.” ECCV (2012).
|
