EyeControl: Wearable Assistance for Industrial Maintenance Tasks

Florian Jungwirth; Benedikt Gollan; Marcel Breitenfellner; Pratheeban Elancheliyan; Alois Ferscha

doi:10.1145/3341162.3348384

EyeControl: Wearable Assistance for Industrial Maintenance Tasks

Florian Jungwirth, Benedikt Gollan, Marcel Breitenfellner, Pratheeban Elancheliyan, Alois Ferscha

Institute of Pervasive Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

Due to the explicit and implicit facets of gaze-based interaction, eye tracking is a major area of interest within the field of cognitive industrial assistance systems. In this position paper, we describe a scenario which includes a wearable platform built around a mobile eye tracker, which can support and guide an industrial worker throughout the execution of a maintenance task. The potential benefits of such a solution are discussed and the key components are outlined.

Original language	English
Title of host publication	Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct)
Editors	Harle, Farrahi, Lane
Publisher	ACM
Pages	628-632
Number of pages	5
ISBN (Electronic)	9781450368698
DOIs	https://doi.org/10.1145/3341162.3348384
Publication status	Published - Sept 2019

Fields of science

202017 Embedded systems
102 Computer Sciences
102009 Computer simulation
102013 Human-computer interaction
102019 Machine learning
102020 Medical informatics
102021 Pervasive computing
102022 Software development
102025 Distributed systems
211902 Assistive technologies
211912 Product design

JKU Focus areas

Digital Transformation

Access to Document

10.1145/3341162.3348384

Cite this

Jungwirth, F., Gollan, B., Breitenfellner, M., Elancheliyan, P., & Ferscha, A. (2019). EyeControl: Wearable Assistance for Industrial Maintenance Tasks. In Harle, Farrahi, Lane (Ed.), Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct) (pp. 628-632). ACM. https://doi.org/10.1145/3341162.3348384

Jungwirth, Florian ; Gollan, Benedikt ; Breitenfellner, Marcel et al. / EyeControl: Wearable Assistance for Industrial Maintenance Tasks. Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct). editor / Harle, Farrahi, Lane. ACM, 2019. pp. 628-632

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title = "EyeControl: Wearable Assistance for Industrial Maintenance Tasks",

abstract = "Due to the explicit and implicit facets of gaze-based interaction, eye tracking is a major area of interest within the field of cognitive industrial assistance systems. In this position paper, we describe a scenario which includes a wearable platform built around a mobile eye tracker, which can support and guide an industrial worker throughout the execution of a maintenance task. The potential benefits of such a solution are discussed and the key components are outlined.",

author = "Florian Jungwirth and Benedikt Gollan and Marcel Breitenfellner and Pratheeban Elancheliyan and Alois Ferscha",

year = "2019",

month = sep,

doi = "10.1145/3341162.3348384",

language = "English",

pages = "628--632",

editor = "\{Harle, Farrahi, Lane\}",

booktitle = "Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC {\textquoteright}19 Adjunct)",

publisher = "ACM",

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Jungwirth, F, Gollan, B, Breitenfellner, M, Elancheliyan, P & Ferscha, A 2019, EyeControl: Wearable Assistance for Industrial Maintenance Tasks. in Harle, Farrahi, Lane (ed.), Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct). ACM, pp. 628-632. https://doi.org/10.1145/3341162.3348384

EyeControl: Wearable Assistance for Industrial Maintenance Tasks. / Jungwirth, Florian; Gollan, Benedikt; Breitenfellner, Marcel et al.
Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct). ed. / Harle, Farrahi, Lane. ACM, 2019. p. 628-632.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

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AU - Elancheliyan, Pratheeban

AU - Ferscha, Alois

PY - 2019/9

Y1 - 2019/9

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AB - Due to the explicit and implicit facets of gaze-based interaction, eye tracking is a major area of interest within the field of cognitive industrial assistance systems. In this position paper, we describe a scenario which includes a wearable platform built around a mobile eye tracker, which can support and guide an industrial worker throughout the execution of a maintenance task. The potential benefits of such a solution are discussed and the key components are outlined.

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BT - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct)

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Jungwirth F, Gollan B, Breitenfellner M, Elancheliyan P, Ferscha A. EyeControl: Wearable Assistance for Industrial Maintenance Tasks. In Harle, Farrahi, Lane, editor, Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct). ACM. 2019. p. 628-632 doi: 10.1145/3341162.3348384

EyeControl: Wearable Assistance for Industrial Maintenance Tasks

Abstract

Fields of science

JKU Focus areas

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EyeControl: Eye-Controlled Machines

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EyeControl: Wearable Assistance for Industrial Maintenance Tasks

Abstract

Fields of science

JKU Focus areas

Access to Document

Other files and links

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EyeControl: Eye-Controlled Machines

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