CamType : assistive text entry using gaze with an off-the-shelf webcam

As modern assistive technology advances, eye-based text entry systems have been developed to help a subset of physically challenged people to improve their communication ability. However, speed of text entry in early eye-typing system tends to be relatively slow due to dwell time. Recently, dwell-fr...

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Main Authors: Liu, Yi, Lee, Bu-Sung, Rajan, Deepu, Sluzek, Andrzej, McKeown, Martin J.
Other Authors: Interdisciplinary Graduate School (IGS)
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/151436
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1514362021-07-09T02:52:06Z CamType : assistive text entry using gaze with an off-the-shelf webcam Liu, Yi Lee, Bu-Sung Rajan, Deepu Sluzek, Andrzej McKeown, Martin J. Interdisciplinary Graduate School (IGS) School of Computer Science and Engineering Nanyang Institute of Technology in Health and Medicine Engineering::Computer science and engineering Assistive Technology Eye-typing System As modern assistive technology advances, eye-based text entry systems have been developed to help a subset of physically challenged people to improve their communication ability. However, speed of text entry in early eye-typing system tends to be relatively slow due to dwell time. Recently, dwell-free methods have been proposed which outperform the dwell-based systems in terms of speed and resilience, but the extra eye-tracking device is still an indispensable equipment. In this article, we propose a prototype of eye-typing system using an off-the-shelf webcam without the extra eye tracker, in which the appearance-based method is proposed to estimate people’s gaze coordinates on the screen based on the frontal face images captured by the webcam. We also investigate some critical issues of the appearance-based method, which helps to improve the estimation accuracy and reduce computing complexity in practice. The performance evaluation shows that eye typing with webcam using the proposed method is comparable to the eye tracker under a small degree of head movement. Nanyang Technological University This work is a collaboration with the Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY). 2021-07-09T02:52:06Z 2021-07-09T02:52:06Z 2019 Journal Article Liu, Y., Lee, B., Rajan, D., Sluzek, A. & McKeown, M. J. (2019). CamType : assistive text entry using gaze with an off-the-shelf webcam. Machine Vision and Applications, 30(3), 407-421. https://dx.doi.org/10.1007/s00138-018-00997-4 0932-8092 0000-0001-7575-2299 https://hdl.handle.net/10356/151436 10.1007/s00138-018-00997-4 2-s2.0-85061457966 3 30 407 421 en Machine Vision and Applications © 2019 Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Assistive Technology
Eye-typing System
spellingShingle Engineering::Computer science and engineering
Assistive Technology
Eye-typing System
Liu, Yi
Lee, Bu-Sung
Rajan, Deepu
Sluzek, Andrzej
McKeown, Martin J.
CamType : assistive text entry using gaze with an off-the-shelf webcam
description As modern assistive technology advances, eye-based text entry systems have been developed to help a subset of physically challenged people to improve their communication ability. However, speed of text entry in early eye-typing system tends to be relatively slow due to dwell time. Recently, dwell-free methods have been proposed which outperform the dwell-based systems in terms of speed and resilience, but the extra eye-tracking device is still an indispensable equipment. In this article, we propose a prototype of eye-typing system using an off-the-shelf webcam without the extra eye tracker, in which the appearance-based method is proposed to estimate people’s gaze coordinates on the screen based on the frontal face images captured by the webcam. We also investigate some critical issues of the appearance-based method, which helps to improve the estimation accuracy and reduce computing complexity in practice. The performance evaluation shows that eye typing with webcam using the proposed method is comparable to the eye tracker under a small degree of head movement.
author2 Interdisciplinary Graduate School (IGS)
author_facet Interdisciplinary Graduate School (IGS)
Liu, Yi
Lee, Bu-Sung
Rajan, Deepu
Sluzek, Andrzej
McKeown, Martin J.
format Article
author Liu, Yi
Lee, Bu-Sung
Rajan, Deepu
Sluzek, Andrzej
McKeown, Martin J.
author_sort Liu, Yi
title CamType : assistive text entry using gaze with an off-the-shelf webcam
title_short CamType : assistive text entry using gaze with an off-the-shelf webcam
title_full CamType : assistive text entry using gaze with an off-the-shelf webcam
title_fullStr CamType : assistive text entry using gaze with an off-the-shelf webcam
title_full_unstemmed CamType : assistive text entry using gaze with an off-the-shelf webcam
title_sort camtype : assistive text entry using gaze with an off-the-shelf webcam
publishDate 2021
url https://hdl.handle.net/10356/151436
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