Current Trends in Human Pupil Localization: A Review

Rasanjalee Rathnayake; Nimantha Madhushan; Ashmini Jeeva; Dhanushika Darshani; Akila Subasinghe; Bhagya Nathali Silva; Lakshitha Prabath Wijesinghe; Udaya Wijenayake

doi:10.1109/ACCESS.2023.3325293

Current Trends in Human Pupil Localization: A Review

Rasanjalee Rathnayake
, Nimantha Madhushan
, Ashmini Jeeva
, Dhanushika Darshani
, Akila Subasinghe
, Bhagya Nathali Silva
, Lakshitha Prabath Wijesinghe
, Udaya Wijenayake^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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Abstract

Pupil localization extracts pupil center coordinates from images and videos of the human eye along with the pupillary boundary. Pupil localization essentially plays a major role in identity verification, disease recognition, visual focus of attention (VFOA) tracking, dementia cognitive assessment, and human fatigue detection. However, the process of pupil localization still remains challenging due to various factors, such as poor-quality images, eye makeup, contact lenses, eyelashes, hair strips, eyebrows, closed eyes, and eye saccades. The pupil localization strategies are essentially divided into learning-based and non-learning-based approaches and discussed in detail with the relevant techniques used. This article aims to deliver the essence of current trends in pupil localization and critically discuss the advantages and disadvantages of each method. Hence, this article can be useful to a broad spectrum of readers as a guide to analyzing the latest trends in pupil localization.

Original language	English
Pages (from-to)	115836-115853
Number of pages	18
Journal	IEEE Access
Volume	11
DOIs	https://doi.org/10.1109/ACCESS.2023.3325293
Publication status	Published - 17 Oct 2023

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Eye and face databases
eye tracking
gaze tracking
iris recognition
learning-based methods
non-learning-based methods
pupil localization

ASJC Scopus subject areas

General Computer Science
General Materials Science
General Engineering

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10.1109/ACCESS.2023.3325293Licence: Creative Commons: Attribution (CC BY)

RathnayakeR2023CurrentFinal published version, 3.83 MBLicence: Creative Commons: Attribution (CC BY)

Cite this

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title = "Current Trends in Human Pupil Localization: A Review",

abstract = "Pupil localization extracts pupil center coordinates from images and videos of the human eye along with the pupillary boundary. Pupil localization essentially plays a major role in identity verification, disease recognition, visual focus of attention (VFOA) tracking, dementia cognitive assessment, and human fatigue detection. However, the process of pupil localization still remains challenging due to various factors, such as poor-quality images, eye makeup, contact lenses, eyelashes, hair strips, eyebrows, closed eyes, and eye saccades. The pupil localization strategies are essentially divided into learning-based and non-learning-based approaches and discussed in detail with the relevant techniques used. This article aims to deliver the essence of current trends in pupil localization and critically discuss the advantages and disadvantages of each method. Hence, this article can be useful to a broad spectrum of readers as a guide to analyzing the latest trends in pupil localization.",

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year = "2023",

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doi = "10.1109/ACCESS.2023.3325293",

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AU - Rathnayake, Rasanjalee

AU - Madhushan, Nimantha

AU - Jeeva, Ashmini

AU - Darshani, Dhanushika

AU - Subasinghe, Akila

AU - Silva, Bhagya Nathali

AU - Wijesinghe, Lakshitha Prabath

AU - Wijenayake, Udaya

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N2 - Pupil localization extracts pupil center coordinates from images and videos of the human eye along with the pupillary boundary. Pupil localization essentially plays a major role in identity verification, disease recognition, visual focus of attention (VFOA) tracking, dementia cognitive assessment, and human fatigue detection. However, the process of pupil localization still remains challenging due to various factors, such as poor-quality images, eye makeup, contact lenses, eyelashes, hair strips, eyebrows, closed eyes, and eye saccades. The pupil localization strategies are essentially divided into learning-based and non-learning-based approaches and discussed in detail with the relevant techniques used. This article aims to deliver the essence of current trends in pupil localization and critically discuss the advantages and disadvantages of each method. Hence, this article can be useful to a broad spectrum of readers as a guide to analyzing the latest trends in pupil localization.

AB - Pupil localization extracts pupil center coordinates from images and videos of the human eye along with the pupillary boundary. Pupil localization essentially plays a major role in identity verification, disease recognition, visual focus of attention (VFOA) tracking, dementia cognitive assessment, and human fatigue detection. However, the process of pupil localization still remains challenging due to various factors, such as poor-quality images, eye makeup, contact lenses, eyelashes, hair strips, eyebrows, closed eyes, and eye saccades. The pupil localization strategies are essentially divided into learning-based and non-learning-based approaches and discussed in detail with the relevant techniques used. This article aims to deliver the essence of current trends in pupil localization and critically discuss the advantages and disadvantages of each method. Hence, this article can be useful to a broad spectrum of readers as a guide to analyzing the latest trends in pupil localization.

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Current Trends in Human Pupil Localization: A Review

Abstract

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this