Classroom Digital Twins with Instrumentation-Free Gaze Tracking
Classroom Digital Twins with Instrumentation-Free Gaze Tracking
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DOI：
10.1145/3411764.3445711
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Karan Ahuja;Deval Shah;Sujeath Pareddy;Françeska Xhakaj;A. Ogan;Yuvraj Agarwal;Chris Harrison
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作者：
Karan Ahuja;Deval Shah;Sujeath Pareddy;Françeska Xhakaj;A. Ogan;Yuvraj Agarwal;Chris Harrison
课堂感知是一个重要且活跃的研究领域，具有改善教学的巨大潜力。作为对专业观察员（当前最佳实践）的补充，自动化教学专业发展系统可以参加每一堂课并捕获所有参与者的细粒度细节。需要捕捉的一个特别有价值的方面是阶级凝视行为。对于学生来说，某些注视模式已被证明与对材料的兴趣相关，而对于教师来说，以学生为中心的注视模式已被证明可以提高可接近性和即时性。不幸的是，现有的教室凝视传感系统的精度有限，并且通常需要专门的外部或佩戴传感器。在这项工作中，我们开发了一种新的计算机视觉驱动系统，为教室的 3D“数字孪生”提供动力，并实现全班 6DOF 头部注视矢量估计，而无需对任何占用者进行检测。我们描述了我们的开源实现，以及对照研究和现实课堂部署的结果。
Classroom sensing is an important and active area of research with great potential to improve instruction. Complementing professional observers – the current best practice – automated pedagogical professional development systems can attend every class and capture fine-grained details of all occupants. One particularly valuable facet to capture is class gaze behavior. For students, certain gaze patterns have been shown to correlate with interest in the material, while for instructors, student-centered gaze patterns have been shown to increase approachability and immediacy. Unfortunately, prior classroom gaze-sensing systems have limited accuracy and often require specialized external or worn sensors. In this work, we developed a new computer-vision-driven system that powers a 3D “digital twin” of the classroom and enables whole-class, 6DOF head gaze vector estimation without instrumenting any of the occupants. We describe our open source implementation, and results from both controlled studies and real-world classroom deployments.