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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bern Open Publishing
2023
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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 |
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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 |
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