Calibration-free text entry using smooth pursuit eye movements

Abdrabou, Yasmeen; Mostafa, Mariam; Khamis, Mohamed; Elmougy, Amr

doi:10.1145/3314111.3319838

Cited by 9 publications

(6 citation statements)

References 18 publications

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“…Moreover, to reduce the number of recalibrations in the experiment, we used a chin rest, which is not a practical solution in most cases. However, while calibration is a necessary part of conventional eye tracking technologies, approaches exist to enable calibration-free eye tracking [29][30][31][32][33], and we expect that this problem could be soon solved in commercial applications. In general, the combined gaze-voice technology necessarily inherits certain issues of the eye tracking-based technology, such as issues in eye pupil tracing in some users, but they could be partly or fully solved with the progress in eye tracking technology.…”

Section: Discussionmentioning

confidence: 99%

Voice as a Mouse Click: Usability and Effectiveness of Simplified Hands-Free Gaze-Voice Selection

et al. 2020

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Voice- and gaze-based hands-free input are increasingly used in human-machine interaction. Attempts to combine them into a hybrid technology typically employ the voice channel as an information-rich channel. Voice seems to be “overqualified” to serve simply as a substitute of a computer mouse click, to confirm selections made by gaze. It could be expected that the user would feel discomfort if they had to frequently make “clicks” using their voice, or easily get bored, which also could lead to low performance. To test this, we asked 23 healthy participants to select moving objects with smooth pursuit eye movements. Manual confirmation of selection was faster and rated as more convenient than voice-based confirmation. However, the difference was not high, especially when voice was used to pronounce objects’ numbers (speech recognition was not applied): Score of convenience (M ± SD) was 9.2 ± 1.1 for manual and 8.0 ± 2.1 for voice confirmation, and time spent per object was 1269 ± 265 ms and 1626 ± 331 ms, respectively. We conclude that “voice-as-click” can be used to confirm selection in gaze-based interaction with computers as a substitute for the computer mouse click when manual confirmation cannot be used.

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Section: Discussionmentioning

confidence: 99%

Voice as a Mouse Click: Usability and Effectiveness of Simplified Hands-Free Gaze-Voice Selection

et al. 2020

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“…Eye movements [1] are investigated a lot for hands-free text entry, whether using gaze interaction(EyeSwipe [22]), blink gestures (BlinkWrite [29], BlinkWrite2 [3]) or eyebrow movements [7]. Lu et al [28] also examined the difference between DwellType, BlinkType and NeckType in virtual reality.…”

Section: Hands-free and Gesture-based Text Entrymentioning

confidence: 99%

“…We conducted an extra study to demonstrate social acceptability for HeadText. Inspired by the survey of social acceptability in HCI [21], we utilized two dimensions for evaluation: (1). the user's social acceptance and (2).…”

Section: Socially Acceptable Text Entrymentioning

confidence: 99%

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HeadText: Exploring Hands-free Text Entry using Head Gestures by Motion Sensing on a Smart Earpiece

Xu¹,

Wang²,

Fang³

et al. 2022

Preprint

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Fig. 1. Application scenarios of HeadText. Fig.a shows that users could perform head gestures to respond to messages when they are eating and their hands are holding the cake. Fig. b presents that a user could use HeadText to input text on a smart watch, whose text entry is originally limited due to the small screen size. Fig.c shows that HeadText could be utilized to help users with motor impairments for text entry. Fig. d presents the application scenario where users could perform head gestures for text entry on the smart glass which is private and socially acceptable in public. We present HeadText, a hands-free technique on a smart earpiece for text entry by motion sensing. Users input text utilizing only head gestures for key selection, word selection, word commitment and word cancelling tasks. Head gesture recognition is supported by motion sensing on a smart earpiece to capture head moving signals and machine learning algorithms (K-Nearest-Neighbor (KNN)with a Dynamic Time Warping (DTW) distance measurement). A 10-participant user study proved that HeadText could recognize head gestures at an accuracy of 94.29%. After that, the second user study presented that HeadText could achieve a maximum accuracy

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“…The smooth-pursuit keyboard SMOOVS uses a one-point calibration to get sufficient accuracy, and is thus almost calibration free. Other works have used a thirdperson calibration, where the eye-tracking system is calibrated by one user, and can be used directly by other users, "calibration free" [Abdrabou et al 2019;Cymek et al 2014;Drewes et al 2019]. The EyeTell application examined in this paper, is the first smoothpursuit based eye-typing application developed using only an iPad and the existing front-facing camera and it does not require any kind of calibration before use.…”

Section: Introductionmentioning

confidence: 99%

EyeTell: Tablet-based Calibration-free Eye-typing using Smooth-pursuit movements

Bafna

Bækgaard

Hansen

2021

ACM Symposium on Eye Tracking Research and Applications

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Gaze tracking technology, with the increasingly robust and lightweight equipment, can have tremendous applications. To use the technology during short interactions, such as in public displays or hospitals to communicate non-verbally after a surgery, the application needs to be intuitive without requiring a calibration. Gaze gestures such as smooth-pursuit eye movements can be detected without calibration. We report the working performance of a calibrationfree eye-typing application using only the front-facing camera of a tablet. In a user study with 29 participants, we obtained an average typing speed of 1.27 WPM after four trials and a maximum typing speed of 1.95 WPM.

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Calibration-free text entry using smooth pursuit eye movements

Cited by 9 publications

References 18 publications

Voice as a Mouse Click: Usability and Effectiveness of Simplified Hands-Free Gaze-Voice Selection

Voice as a Mouse Click: Usability and Effectiveness of Simplified Hands-Free Gaze-Voice Selection

HeadText: Exploring Hands-free Text Entry using Head Gestures by Motion Sensing on a Smart Earpiece

EyeTell: Tablet-based Calibration-free Eye-typing using Smooth-pursuit movements

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