Gaze Analysis System for Immersive 360° Video for Preservice Teacher Education
Gaze Analysis System for Immersive 360° Video for Preservice Teacher Education
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DOI：
10.1145/3581783.3613908
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发表时间：
2023-10
期刊：
影响因子：
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通讯作者：
Chris Lenart;Pegah Ahadian;Yuxin Yang;Simon Suo;Ashton Corsello;K. Kosko;Qiang Guan
中科院分区：
文献类型：
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作者：
Chris Lenart;Pegah Ahadian;Yuxin Yang;Simon Suo;Ashton Corsello;K. Kosko;Qiang Guan
多传感器设备的统一系统，特别是虚拟现实（VR）中的眼动跟踪，非常复杂，通常需要监听和流式传输多通道数据。在这个项目中，我们提出了一个视觉分析框架，用于复制参与者的观看参与，通过将头部运动解释为旋转和凝视点（POG）作为屏幕上的指标。我们的解决方案建议增加一层系统，用于近实时处理和分析多设备数据，以与数据连接，并实现整个VR眼动跟踪会话的近实时或后续离线查看。此外，我们的方法提供了一个不需要电池的解决方案来创建传统的眼动跟踪可视化技术。最后，我们应用三个先前的教育技术分析指标：更高的密度凝视的学生，更短的固定时间，和更少的固定持续时间的变化，为学生确定在这个系统中的专业知识水平。我们系统地建立了一个无处不在的，多设备，眼动跟踪解决方案，以纳入这种方法。我们通过用户研究评估我们的系统的有效性，使用专业知识和非专业知识水平，并选择性地调查，以确定复制的经验的质量，我们通过运行一个真实世界的用户研究与64个不同的参与者测试系统。我们证明了该应用程序的意义和潜力，整合以前的分析指标使用收集的数据，该数据收集和分析已被IRB批准。
Unified systems for multi-sensor devices, particularly eye-tracking in Virtual Reality (VR), are intricate and often require the listening and streaming of multichannel data. In this project, we propose a visual analysis framework for replicating a participant's viewing involvement by interpreting head movements as rotations and point-of-gaze (POG) as on-screen indicators. Our solution suggests an additional layer of system for near-real-time for processing and analyzing this multi-device data to connect with the data and enable both near-real-time or subsequent offline viewing of the entire VR eye-tracking session. Moreover, our method provides a no-batteries-need solution to create traditional eye-tracking visualization techniques. Finally, we apply three prior education technology analysis metrics: higher density gaze for students, shorter fixation time, and less fixation duration variance for students to determine expertise levels in this system. We systematically establish a ubiquitous, multi-device, eye-tracking solution to incorporate this approach. We evaluate the effectiveness of our system through a user study, using both expertise and non- expertise levels, and selectively surveying to ascertain the quality of the replicated experience and we test the system by running a real-world user study with sixty four different participants. We demonstrate the application's significance and potential to integrate prior analysis metrics using the collected data which this data collection and analysis have been approved by IRB.