Evaluating User Experience and Data Quality in Gamified Data Collection for Appearance-Based Gaze Estimation
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866916378301169664 |
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| author | Yue, Mingtao Sayuda, Tomomi Pennington, Miles Sugano, Yusuke |
| author_facet | Yue, Mingtao Sayuda, Tomomi Pennington, Miles Sugano, Yusuke |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14095 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Evaluating User Experience and Data Quality in Gamified Data Collection for Appearance-Based Gaze Estimation Yue, Mingtao Sayuda, Tomomi Pennington, Miles Sugano, Yusuke Human-Computer Interaction 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. |
| title | Evaluating User Experience and Data Quality in Gamified Data Collection for Appearance-Based Gaze Estimation |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2401.14095 |