Pupil Localisation and Eye Centre Estimation using Machine Learning and Computer Vision
- Submitting institution
-
University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 33938
- Type
- D - Journal article
- DOI
-
10.3390/s20133785
- Title of journal
- Sensors
- Article number
- -
- First page
- 1
- Volume
- 20
- Issue
- 13
- ISSN
- 1424-8220
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
A - Aerospace and Sensing Group
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper was distinguished as a “feature paper” by the publisher, MDPI. It describes research funded by Prince Sattam bin Abdulaziz University, KSA under grant number: 2020/01/1174. It is the first to suggest how an issue associated with the accurate localisation of the gaze in low light conditions can be resolved, leading to possibilities for the development of a diverse range of industrial applications related to human-computer interfaces in low light (e.g., fatigue detection, human identification in low light conditions).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
