The Eye Tracking and Gaze Estimation System by Low Cost Wearable Devices

This paper describes a low-cost, robust, and accurate remote eye-tracking system that uses an industrial prototype smartphone with integrated infrared illumination and camera. Numerous studies have demonstrated the beneficial use of eye-tracking in domains such as neurological and neuropsychiatric testing, advertising evaluation, pilot training, and automotive safety. Remote eye-tracking on a smartphone could enable the significant growth in the deployment of applications in these domains. Our system uses a 3D gaze-estimation model that enables accurate point-of-gaze (PoG) estimation with free head and device motion. To accurately determine the input eye features (pupil center and corneal reflections), the system uses Convolutional Neural Networks (CNNs) together with a novel center-of-mass output layer. The use of CNNs improves the system’s robustness to the significant variability in the appearance of eye-images found in handheld eye trackers. The system was tested with 8 subjects with the device free to move in their hands and produced a gaze bias of 0.72°. Our hybrid approach that uses artificial illumination, a 3D gaze-estimation model, and a CNN feature extractor achieved an accuracy that is significantly (400%) better than current eye-tracking systems on smartphones that use natural illumination and machine-learning techniques to estimate the PoG.

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Low Cost Eye Tracking: The Current Panorama

Computational Intelligence and Neuroscience ◽

10.1155/2016/8680541 ◽

2016 ◽

Vol 2016 ◽

pp. 1-14 ◽

Cited By ~ 26

Author(s):

Onur Ferhat ◽

Fernando Vilariño

Keyword(s):

Eye Tracking ◽

Visible Light ◽

Open Source ◽

Low Cost ◽

Gaze Estimation ◽

Head Pose ◽

Gaze Tracking ◽

Estimation Techniques ◽

Public Datasets ◽

Interesting Alternative

Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools.

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Low-Cost Eye Tracking Calibration: A Knowledge-Based Study

Sensors ◽

10.3390/s21155109 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5109

Author(s):

Gonzalo Garde ◽

Andoni Larumbe-Bergera ◽

Benoît Bossavit ◽

Sonia Porta ◽

Rafael Cabeza ◽

...

Keyword(s):

Eye Tracking ◽

High Performance ◽

Low Cost ◽

Image Features ◽

Gaze Estimation ◽

Low Resolution ◽

Knowledge Based ◽

Fully Connected ◽

The Impact ◽

Selection Of

Subject calibration has been demonstrated to improve the accuracy in high-performance eye trackers. However, the true weight of calibration in off-the-shelf eye tracking solutions is still not addressed. In this work, a theoretical framework to measure the effects of calibration in deep learning-based gaze estimation is proposed for low-resolution systems. To this end, features extracted from the synthetic U2Eyes dataset are used in a fully connected network in order to isolate the effect of specific user’s features, such as kappa angles. Then, the impact of system calibration in a real setup employing I2Head dataset images is studied. The obtained results show accuracy improvements over 50%, probing that calibration is a key process also in low-resolution gaze estimation scenarios. Furthermore, we show that after calibration accuracy values close to those obtained by high-resolution systems, in the range of 0.7∘, could be theoretically obtained if a careful selection of image features was performed, demonstrating significant room for improvement for off-the-shelf eye tracking systems.

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Low cost human-robot gaze estimation system

Proceedings of the 26th Australian Computer-Human Interaction Conference on Designing Futures the Future of Design - OzCHI '14 ◽

10.1145/2686612.2686674 ◽

2014 ◽

Author(s):

Karlos Ishac ◽

David Rozado

Keyword(s):

Low Cost ◽

Gaze Estimation ◽

Estimation System

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Automatic pupil detection and gaze estimation using the vestibulo-ocular reflex in a low-cost eye-tracking setup

SAIEE Africa Research Journal ◽

10.23919/saiee.2020.9142605 ◽

2020 ◽

Vol 111 (3) ◽

pp. 120-124 ◽

Cited By ~ 2

Author(s):

Vered Aharonson ◽

Verushen Y. Coopoo ◽

Kyle L. Govender ◽

Michiel Postema

Keyword(s):

Eye Tracking ◽

Low Cost ◽

Gaze Estimation ◽

Ocular Reflex ◽

Pupil Detection ◽

Vestibulo Ocular Reflex

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Gaze Estimation Method Using Analysis of Electrooculogram Signals and Kinect Sensor

Computational Intelligence and Neuroscience ◽

10.1155/2017/2074752 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Keiko Sakurai ◽

Mingmin Yan ◽

Koichi Tanno ◽

Hiroki Tamura

Keyword(s):

Eye Movements ◽

Eye Tracking ◽

Estimation Method ◽

Gaze Estimation ◽

Strongly Correlated ◽

Kinect Sensor ◽

Tracking Method ◽

Estimation System ◽

Communication Methods ◽

Very High

A gaze estimation system is one of the communication methods for severely disabled people who cannot perform gestures and speech. We previously developed an eye tracking method using a compact and light electrooculogram (EOG) signal, but its accuracy is not very high. In the present study, we conducted experiments to investigate the EOG component strongly correlated with the change of eye movements. The experiments in this study are of two types: experiments to see objects only by eye movements and experiments to see objects by face and eye movements. The experimental results show the possibility of an eye tracking method using EOG signals and a Kinect sensor.

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Homography-Based Low-Cost Gaze Estimation and its Application to the Usability Assessment of Digital Prototypes of Information Appliances

Volume 2B: 33rd Computers and Information in Engineering Conference ◽

10.1115/detc2013-12931 ◽

2013 ◽

Cited By ~ 1

Author(s):

Satoshi Kanai ◽

Hiroaki Date

Keyword(s):

Low Cost ◽

Test Session ◽

Gaze Estimation ◽

Ui Design ◽

The Gaze ◽

Usability Assessment ◽

Simple Event ◽

Information Appliances ◽

Estimation System ◽

Digital Prototype

Recently 3D digital prototypes of information appliances have been proposed for efficient user acceptance tests of user-interface (UI) usability. The purpose of this research is to develop a gaze estimation system based on Homography and to fully integrate it with a 3D digital prototype of the information appliances in order to obtain information more useful for usability assessment. The estimation system consists only of four infrared LEDs and a USB camera and is low-cost. The gaze estimation enables the system not only to record a gaze point on the prototype but to identify the UI objects which the user is looking for in real time during the test session. A gaze-based index was newly introduced to identify the misleading UI objects and to quantify the irrelevance of the UI design. A case study suggested that the integration of the gaze estimation with the 3D digital prototype and the proposed index were useful for automatically identifying which irrelevant UI objects misled the users’ operations which could not yet be captured in previous simple event logging of the user inputs.

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