Cargando…

GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration

Gaze input, i.e., information input via eye of users, represents a promising method for contact- free interaction in human-machine systems. In this paper, we present the GazeVending interface (GaVe), which lets users control actions on a display with their eyes. The interface works on a regular webc...

Descripción completa

Detalles Bibliográficos
Autores principales: Zeng, Zhe, Liu, Sai, Cheng, Hao, Liu, Hailong, Li, Yang, Feng, Yu, Siebert, Felix Wilhelm
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bern Open Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640920/
https://www.ncbi.nlm.nih.gov/pubmed/38022900
http://dx.doi.org/10.16910/jemr.16.1.2
_version_ 1785133854017716224
author Zeng, Zhe
Liu, Sai
Cheng, Hao
Liu, Hailong
Li, Yang
Feng, Yu
Siebert, Felix Wilhelm
author_facet Zeng, Zhe
Liu, Sai
Cheng, Hao
Liu, Hailong
Li, Yang
Feng, Yu
Siebert, Felix Wilhelm
author_sort Zeng, Zhe
collection PubMed
description Gaze input, i.e., information input via eye of users, represents a promising method for contact- free interaction in human-machine systems. In this paper, we present the GazeVending interface (GaVe), which lets users control actions on a display with their eyes. The interface works on a regular webcam, available on most of today's laptops, and only requires a short one-point calibration before use. GaVe is designed in a hierarchical structure, presenting broad item cluster to users first and subsequently guiding them through another selection round, which allows the presentation of a large number of items. Cluster/item selection in GaVe is based on the dwell time, i.e., the time duration that users look at a given Cluster/ item. A user study (N=22) was conducted to test optimal dwell time thresholds and comfortable human-to-display distances. Users' perception of the system, as well as error rates and task completion time were registered. We found that all participants were able to quickly understand and know how to interact with the interface, and showed good performance, selecting a target item within a group of 12 items in 6.76 seconds on average. We provide design guidelines for GaVe and discuss the potentials of the system.
format Online
Article
Text
id pubmed-10640920
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Bern Open Publishing
record_format MEDLINE/PubMed
spelling pubmed-106409202023-01-25 GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration Zeng, Zhe Liu, Sai Cheng, Hao Liu, Hailong Li, Yang Feng, Yu Siebert, Felix Wilhelm J Eye Mov Res Research Article Gaze input, i.e., information input via eye of users, represents a promising method for contact- free interaction in human-machine systems. In this paper, we present the GazeVending interface (GaVe), which lets users control actions on a display with their eyes. The interface works on a regular webcam, available on most of today's laptops, and only requires a short one-point calibration before use. GaVe is designed in a hierarchical structure, presenting broad item cluster to users first and subsequently guiding them through another selection round, which allows the presentation of a large number of items. Cluster/item selection in GaVe is based on the dwell time, i.e., the time duration that users look at a given Cluster/ item. A user study (N=22) was conducted to test optimal dwell time thresholds and comfortable human-to-display distances. Users' perception of the system, as well as error rates and task completion time were registered. We found that all participants were able to quickly understand and know how to interact with the interface, and showed good performance, selecting a target item within a group of 12 items in 6.76 seconds on average. We provide design guidelines for GaVe and discuss the potentials of the system. Bern Open Publishing 2023-01-25 /pmc/articles/PMC10640920/ /pubmed/38022900 http://dx.doi.org/10.16910/jemr.16.1.2 Text en Copyright (©) 2023 Zhe Zeng, Sai Liu, Hao Cheng, Hailong Liu, Yang Li, Yu Feng, Felix Wilhelm Siebert https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License, ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Research Article
Zeng, Zhe
Liu, Sai
Cheng, Hao
Liu, Hailong
Li, Yang
Feng, Yu
Siebert, Felix Wilhelm
GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration
title GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration
title_full GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration
title_fullStr GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration
title_full_unstemmed GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration
title_short GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration
title_sort gave: a webcam-based gaze vending interface using one-point calibration
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640920/
https://www.ncbi.nlm.nih.gov/pubmed/38022900
http://dx.doi.org/10.16910/jemr.16.1.2
work_keys_str_mv AT zengzhe gaveawebcambasedgazevendinginterfaceusingonepointcalibration
AT liusai gaveawebcambasedgazevendinginterfaceusingonepointcalibration
AT chenghao gaveawebcambasedgazevendinginterfaceusingonepointcalibration
AT liuhailong gaveawebcambasedgazevendinginterfaceusingonepointcalibration
AT liyang gaveawebcambasedgazevendinginterfaceusingonepointcalibration
AT fengyu gaveawebcambasedgazevendinginterfaceusingonepointcalibration
AT siebertfelixwilhelm gaveawebcambasedgazevendinginterfaceusingonepointcalibration