An Eye-Tracking Dataset for Visual Attention Modelling in a Virtual Museum Context

被引：5
|
作者：
Zhou, Yunzhan [1 ,2 ]
Feng, Tian [1 ]
Shuai, Shihui [2 ]
Li, Xiangdong [2 ]
Sun, Lingyun [2 ]
Duh, Henry B. L. [1 ]
机构：
[1] La Trobe Univ, Bundoora, Vic, Australia
[2] Zhejiang Univ, Hangzhou, Peoples R China
来源：
17TH ACM SIGGRAPH INTERNATIONAL CONFERENCE ON VIRTUAL-REALITY CONTINUUM AND ITS APPLICATIONS IN INDUSTRY (VRCAI 2019) | 2019年
关键词：
eye-tracking datasets; neural networks; gaze detection; visual attention;
D O I：
10.1145/3359997.3365738
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Predicting the user's visual attention enables a virtual reality (VR) environment to provide a context-aware and interactive user experience. Researchers have attempted to understand visual attention using eye-tracking data in a 2D plane. In this poster, we propose the first 3D eye-tracking dataset for visual attention modelling in the context of a virtual museum. It comprises about 7 million records and may facilitate visual attention modelling in a 3D VR space.
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页数：3
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