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FaceSync:用于通过头戴式摄像头记录面部表情的开源框架。

FaceSync: Open source framework for recording facial expressions with head-mounted cameras.

作者信息

Cheong Jin Hyun, Brooks Sawyer, Chang Luke J

机构信息

Psychological and Brain Sciences, Dartmouth College, Hanover, NH, 03755, USA.

Department of Neuroscience, Oberlin College, Oberlin, Ohio, 44074, USA.

出版信息

F1000Res. 2019 May 21;8:702. doi: 10.12688/f1000research.18187.1. eCollection 2019.

Abstract

Advances in computer vision and machine learning algorithms have enabled researchers to extract facial expression data from face video recordings with greater ease and speed than standard manual coding methods, which has led to a dramatic increase in the pace of facial expression research. However, there are many limitations in recording facial expressions in laboratory settings.  Conventional video recording setups using webcams, tripod-mounted cameras, or pan-tilt-zoom cameras require making compromises between cost, reliability, and flexibility. As an alternative, we propose the use of a mobile head-mounted camera that can be easily constructed from our open-source instructions and blueprints at a fraction of the cost of conventional setups. The head-mounted camera framework is supported by the open source Python toolbox FaceSync, which provides an automated method for synchronizing videos. We provide four proof-of-concept studies demonstrating the benefits of this recording system in reliably measuring and analyzing facial expressions in diverse experimental setups, including group interaction experiments.

摘要

计算机视觉和机器学习算法的进步使研究人员能够比标准手动编码方法更轻松、快速地从面部视频记录中提取面部表情数据,这导致面部表情研究的步伐大幅加快。然而,在实验室环境中记录面部表情存在许多限制。使用网络摄像头、三脚架安装的相机或云台变焦相机的传统视频录制设置需要在成本、可靠性和灵活性之间做出妥协。作为一种替代方案,我们建议使用一种可移动的头戴式相机,它可以根据我们的开源说明和蓝图轻松构建,成本仅为传统设置的一小部分。头戴式相机框架由开源Python工具箱FaceSync支持,该工具箱提供了一种自动同步视频的方法。我们提供了四项概念验证研究,证明了该记录系统在各种实验设置(包括群体互动实验)中可靠地测量和分析面部表情的好处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9921/7059847/b3ab222ae62f/f1000research-8-19894-g0000.jpg

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