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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 3/2019

12.02.2019 | Original Paper

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

verfasst von: Yi Liu, Bu-Sung Lee, Deepu Rajan, Andrzej Sluzek, Martin J. McKeown

Erschienen in: Machine Vision and Applications | Ausgabe 3/2019

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Abstract

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.
Vorheriger Artikel Saliency object detection: integrating reconstruction and prior
Nächster Artikel Major automatic diabetic retinopathy screening systems and related core algorithms: a review

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Metadaten
Titel
CamType: assistive text entry using gaze with an off-the-shelf webcam
verfasst von
Yi Liu
Bu-Sung Lee
Deepu Rajan
Andrzej Sluzek
Martin J. McKeown
Publikationsdatum
12.02.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 3/2019
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-018-00997-4

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