arXiv Open Access 2024

Evaluating User Experience and Data Quality in Gamified Data Collection for Appearance-Based Gaze Estimation

Mingtao Yue Tomomi Sayuda Miles Pennington Yusuke Sugano
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Abstrak

Appearance-based gaze estimation, which uses only a regular camera to estimate human gaze, is important in various application fields. While the technique faces data bias issues, data collection protocol is often demanding, and collecting data from a wide range of participants is difficult. It is an important challenge to design opportunities that allow a diverse range of people to participate while ensuring the quality of the training data. To tackle this challenge, we introduce a novel gamified approach for collecting training data. In this game, two players communicate words via eye gaze through a transparent letter board. Images captured during gameplay serve as valuable training data for gaze estimation models. The game is designed as a physical installation that involves communication between players, and it is expected to attract the interest of diverse participants. We assess the game's significance on data quality and user experience through a comparative user study.

Topik & Kata Kunci

Penulis (4)

M

Mingtao Yue

T

Tomomi Sayuda

M

Miles Pennington

Y

Yusuke Sugano

Format Sitasi

Yue, M., Sayuda, T., Pennington, M., Sugano, Y. (2024). Evaluating User Experience and Data Quality in Gamified Data Collection for Appearance-Based Gaze Estimation. https://arxiv.org/abs/2401.14095

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Tahun Terbit
2024
Bahasa
en
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arXiv
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Open Access ✓