Bruckert Alexandre, Christie Marc, Le Meur Olivier
University of Rennes 1, IRISA, CNRS, Rennes, France.
Behav Res Methods. 2023 Sep;55(6):2940-2959. doi: 10.3758/s13428-022-01949-7. Epub 2022 Aug 24.
In the process of making a movie, directors constantly care about where the spectator will look on the screen. Shot composition, framing, camera movements, or editing are tools commonly used to direct attention. In order to provide a quantitative analysis of the relationship between those tools and gaze patterns, we propose a new eye-tracking database, containing gaze-pattern information on movie sequences, as well as editing annotations, and we show how state-of-the-art computational saliency techniques behave on this dataset. In this work, we expose strong links between movie editing and spectators gaze distributions, and open several leads on how the knowledge of editing information could improve human visual attention modeling for cinematic content. The dataset generated and analyzed for this study is available at https://github.com/abruckert/eye_tracking_filmmaking.
在制作电影的过程中,导演们始终关注观众在屏幕上的视线落点。镜头构图、取景、镜头运动或剪辑都是引导注意力常用的手段。为了对这些手段与注视模式之间的关系进行定量分析,我们提出了一个新的眼动追踪数据库,其中包含电影片段的注视模式信息以及剪辑标注,并且展示了当前最先进的计算显著性技术在该数据集上的表现。在这项工作中,我们揭示了电影剪辑与观众注视分布之间的紧密联系,并开启了几条关于如何利用剪辑信息知识改进电影内容的人类视觉注意力建模的思路。本研究生成并分析的数据集可在https://github.com/abruckert/eye_tracking_filmmaking获取。