Next Article in Journal
Review of Health Monitoring Techniques for Capacitors Used in Power Electronics Converters
Next Article in Special Issue
Walking Strategies and Performance Evaluation for Human-Exoskeleton Systems under Admittance Control
Previous Article in Journal
LSTM-Based VAE-GAN for Time-Series Anomaly Detection
Previous Article in Special Issue
Hybrid Coils-Based Wireless Power Transfer for Intelligent Sensors
Review

When I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking

by 1,†, 2,*,†, 2 and 1
1
Interdisciplinary Center for Security, Reliability and Trust (SnT), University of Luxembourg, L-4364 Esch-sur-Alzette, Luxembourg
2
National Research Council of Italy—Institute of Applied Sciences and Intelligent Systems, 73100 Lecce, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2020, 20(13), 3739; https://doi.org/10.3390/s20133739
Received: 19 May 2020 / Revised: 18 June 2020 / Accepted: 30 June 2020 / Published: 3 July 2020
(This article belongs to the Special Issue Sensor-Based Assistive Devices and Technology)
The automatic detection of eye positions, their temporal consistency, and their mapping into a line of sight in the real world (to find where a person is looking at) is reported in the scientific literature as gaze tracking. This has become a very hot topic in the field of computer vision during the last decades, with a surprising and continuously growing number of application fields. A very long journey has been made from the first pioneering works, and this continuous search for more accurate solutions process has been further boosted in the last decade when deep neural networks have revolutionized the whole machine learning area, and gaze tracking as well. In this arena, it is being increasingly useful to find guidance through survey/review articles collecting most relevant works and putting clear pros and cons of existing techniques, also by introducing a precise taxonomy. This kind of manuscripts allows researchers and technicians to choose the better way to move towards their application or scientific goals. In the literature, there exist holistic and specifically technological survey documents (even if not updated), but, unfortunately, there is not an overview discussing how the great advancements in computer vision have impacted gaze tracking. Thus, this work represents an attempt to fill this gap, also introducing a wider point of view that brings to a new taxonomy (extending the consolidated ones) by considering gaze tracking as a more exhaustive task that aims at estimating gaze target from different perspectives: from the eye of the beholder (first-person view), from an external camera framing the beholder’s, from a third-person view looking at the scene where the beholder is placed in, and from an external view independent from the beholder. View Full-Text
Keywords: gaze tracking; gaze estimation; survey; review; computer vision gaze tracking; gaze estimation; survey; review; computer vision
Show Figures

Figure 1

MDPI and ACS Style

Cazzato, D.; Leo, M.; Distante, C.; Voos, H. When I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking. Sensors 2020, 20, 3739. https://doi.org/10.3390/s20133739

AMA Style

Cazzato D, Leo M, Distante C, Voos H. When I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking. Sensors. 2020; 20(13):3739. https://doi.org/10.3390/s20133739

Chicago/Turabian Style

Cazzato, Dario, Marco Leo, Cosimo Distante, and Holger Voos. 2020. "When I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking" Sensors 20, no. 13: 3739. https://doi.org/10.3390/s20133739

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop