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    <titleInfo>
        <title>Tracing shapes with eyes</title>
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    <name type="personal">
        <namePart type="given">Mohammad</namePart>
        <namePart type="given">Rakib</namePart>
        <namePart type="family">Hasan</namePart>
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    <name type="personal">
        <namePart type="given">Debajyoti</namePart>
        <namePart type="family">Mondal</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Carl</namePart>
        <namePart type="family">Gutwin</namePart>
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            <title>Proceedings of the 11th Augmented Human International Conference</title>
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    <abstract>Eye tracking systems can provide people with severe motor impairments a way to communicate through gaze-based interactions. Such systems transform a user’s gaze input into mouse pointer coordinates that can trigger keystrokes on an on-screen keyboard. However, typing using this approach requires large back-and-forth eye movements, and the required effort depends both on the length of the text and the keyboard layout. Motivated by the idea of sketch-based image search, we explore a gaze-based approach where users draw a shape on a sketchpad using gaze input, and the shape is used to search for similar letters, words, and other predefined controls. The sketch-based approach is area efficient (compared to an on-screen keyboard), allows users to create custom commands, and creates opportunities for gaze-based authentication. Since variation in the drawn shapes makes the search difficult, the system can show a guide (e.g., a 14-segment digital display) on the sketchpad so that users can trace their desired shape. In this paper, we take a first step that investigates the feasibility of the sketch-based approach, by examining how well users can trace a given shape using gaze input. We designed an interface where participants traced a set of given shapes. We then compared the similarity of the drawn and traced shapes. Our study results show the potential of the sketch-based approach: users were able to trace shapes reasonably well using gaze input, even for complex shapes involving three letters; shape tracing accuracy for gaze was better than ‘free-form’ hand drawing. We also report on how different shape complexities influence the time and accuracy of the shape tracing tasks.</abstract>
    <identifier type="citekey">Hasan-2020-Tracing</identifier>
    <identifier type="doi">10.1145/3396339.3396390</identifier>
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        <url>https://gwf-uwaterloo.github.io/gwf-publications/G20-86001</url>
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        <date>2020</date>
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%0 Journal Article
%T Tracing shapes with eyes
%A Hasan, Mohammad Rakib
%A Mondal, Debajyoti
%A Gutwin, Carl
%J Proceedings of the 11th Augmented Human International Conference
%D 2020
%I ACM
%F Hasan-2020-Tracing
%X Eye tracking systems can provide people with severe motor impairments a way to communicate through gaze-based interactions. Such systems transform a user’s gaze input into mouse pointer coordinates that can trigger keystrokes on an on-screen keyboard. However, typing using this approach requires large back-and-forth eye movements, and the required effort depends both on the length of the text and the keyboard layout. Motivated by the idea of sketch-based image search, we explore a gaze-based approach where users draw a shape on a sketchpad using gaze input, and the shape is used to search for similar letters, words, and other predefined controls. The sketch-based approach is area efficient (compared to an on-screen keyboard), allows users to create custom commands, and creates opportunities for gaze-based authentication. Since variation in the drawn shapes makes the search difficult, the system can show a guide (e.g., a 14-segment digital display) on the sketchpad so that users can trace their desired shape. In this paper, we take a first step that investigates the feasibility of the sketch-based approach, by examining how well users can trace a given shape using gaze input. We designed an interface where participants traced a set of given shapes. We then compared the similarity of the drawn and traced shapes. Our study results show the potential of the sketch-based approach: users were able to trace shapes reasonably well using gaze input, even for complex shapes involving three letters; shape tracing accuracy for gaze was better than ‘free-form’ hand drawing. We also report on how different shape complexities influence the time and accuracy of the shape tracing tasks.
%R 10.1145/3396339.3396390
%U https://gwf-uwaterloo.github.io/gwf-publications/G20-86001
%U https://doi.org/10.1145/3396339.3396390

Markdown (Informal)

[Tracing shapes with eyes](https://gwf-uwaterloo.github.io/gwf-publications/G20-86001) (Hasan et al., GWF 2020)

• Tracing shapes with eyes (Hasan et al., GWF 2020)

ACL

• Mohammad Rakib Hasan, Debajyoti Mondal, and Carl Gutwin. 2020. Tracing shapes with eyes. Proceedings of the 11th Augmented Human International Conference.