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.

翻译：外观眼动估计仅利用常规摄像头估计人类视线方向，在多个应用领域具有重要意义。然而该技术面临数据偏差问题，数据采集协议通常要求苛刻，且难以从广泛参与者中收集数据。如何设计既能吸引多元化人群参与又能保证训练数据质量的采集方案，成为重要挑战。为应对这一挑战，我们提出一种新颖的游戏化训练数据收集方法。在该游戏中，两名玩家通过透明字母板以视线进行文字交流，游戏过程中捕获的图像可作为眼动估计模型的宝贵训练数据。游戏被设计为涉及玩家间互动的实体装置，预期能吸引不同背景参与者的兴趣。我们通过对比用户研究评估了该游戏对数据质量和用户体验的影响。