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一项基于高密度脑电图的研究,旨在探索虚拟现实电影剪辑和认知事件分割理论。

A High-Density EEG Study Investigating VR Film Editing and Cognitive Event Segmentation Theory.

机构信息

Shanghai Film Academy, Shanghai University, Shanghai 200072, China.

Shanghai Film Special Effects Engineering Technology Research Center, Shanghai University, Shanghai 200072, China.

出版信息

Sensors (Basel). 2021 Oct 28;21(21):7176. doi: 10.3390/s21217176.

Abstract

This paper introduces a cognitive psychological experiment that was conducted to analyze how traditional film editing methods and the application of cognitive event segmentation theory perform in virtual reality (VR). Thirty volunteers were recruited and asked to watch a series of short VR videos designed in three dimensions: time, action (characters), and space. Electroencephalograms (EEG) were recorded simultaneously during their participation. Subjective results show that any of the editing methods used would lead to an increased load and reduced immersion. Furthermore, the cognition of event segmentation theory also plays an instructive role in VR editing, with differences mainly focusing on frontal, parietal, and central regions. On this basis, visual evoked potential (VEP) analysis was performed, and the standardized low-resolution brain electromagnetic tomography algorithm (sLORETA) traceability method was used to analyze the data. The results of the VEP analysis suggest that shearing usually elicits a late event-related potential component, while the sources of VEP are mainly the frontal and parietal lobes. The insights derived from this work can be used as guidance for VR content creation, allowing VR image editing to reveal greater richness and unique beauty.

摘要

本文介绍了一项认知心理学实验,旨在分析传统电影剪辑方法和认知事件分割理论在虚拟现实(VR)中的应用。招募了 30 名志愿者,要求他们观看一系列设计成三维的短 VR 视频:时间、动作(角色)和空间。在他们参与的同时,记录脑电图(EEG)。主观结果表明,使用任何剪辑方法都会导致负载增加和沉浸感降低。此外,事件分割理论的认知在 VR 编辑中也具有指导作用,差异主要集中在前额、顶叶和中央区域。在此基础上,进行了视觉诱发电位(VEP)分析,并采用标准化低分辨率脑电磁断层扫描算法(sLORETA)轨迹法对数据进行分析。VEP 分析的结果表明,剪切通常会引起晚期事件相关电位成分,而 VEP 的源主要是额叶和顶叶。这项工作的启示可用于指导 VR 内容创作,使 VR 图像编辑能够展现出更丰富和独特的美。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d00/8586935/62ae480f053e/sensors-21-07176-g001.jpg

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