数据2MV - 用于多视图场景的用户行为数据集
Tiago Soares da Costa1, Maria Teresa Andrade2,1, Paula Viana3,1
1Centre for Telecommunications and Multimedia, INESC TEC, Porto, Portugal.
Data in brief
|November 29, 2023
概括
Data2MV数据集提供了来自45名观看视频的参与者的宝贵视线固定数据,有助于研究沉浸式流媒体. 这一数据集包括超过一百万的凝视定位和相关的突出地图.
科学领域:
- 计算机视觉 计算机视觉
- 人与计算机的交互
- 多媒体系统 多媒体系统
背景情况:
- 视线跟踪数据对于理解多媒体环境中的用户行为至关重要.
- 缺乏全面的数据集阻碍了对沉浸式,多视图流媒体场景的研究.
- 现有的数据集往往缺乏高级分析所需的规模和细节.
研究的目的:
- 引入和发布Data2MV数据集,这是一个新的凝视定位数据集合.
- 为研究人员提供丰富的资源,用于研究视频消费中的视觉注意力.
- 支持开发用于突出性预测和用户行为分析的新算法.
主要方法:
- 采集了45名参与者使用英特尔RealSense F200摄像机的凝视固定数据.
- 使用了七个20分钟的视频播放列表,数据以0.05秒的间隔记录.
- 从聚合的固定数据和提供的开源软件工具生成突出地图.
主要成果:
- 该数据集包括128个实验中的1000,845个凝视定位.
- 包括68,393个图像和同样数量的聚合突出地图.
- 数据2MV数据集在Mendeley数据上公开提供.
结论:
- 数据2MV数据集解决了沉浸式流媒体中凝视定位数据的稀缺问题.
- 它是推动视觉注意力和HCI研究的宝贵资源.
- 促进了显著性和用户行为的计算模型的开发和验证.
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