Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Section of Speech and Language Pathology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Atten Percept Psychophys. 2024 Oct;86(7):2221-2230. doi: 10.3758/s13414-023-02679-4. Epub 2023 Apr 26.
Quantification of face-to-face interaction can provide highly relevant information in cognitive and psychological science research. Current commercial glint-dependent solutions suffer from several disadvantages and limitations when applied in face-to-face interaction, including data loss, parallax errors, the inconvenience and distracting effect of wearables, and/or the need for several cameras to capture each person. Here we present a novel eye-tracking solution, consisting of a dual-camera system used in conjunction with an individually optimized deep learning approach that aims to overcome some of these limitations. Our data show that this system can accurately classify gaze location within different areas of the face of two interlocutors, and capture subtle differences in interpersonal gaze synchrony between two individuals during a (semi-)naturalistic face-to-face interaction.
面对面互动的量化可以为认知和心理科学研究提供高度相关的信息。当前商业的基于闪光的解决方案在应用于面对面互动时存在一些缺点和限制，包括数据丢失、视差误差、可穿戴设备的不便和分散注意力的影响，以及/或者需要多个摄像头来捕捉每个人。在这里，我们提出了一种新的眼动追踪解决方案，由一个双摄像头系统与一个单独优化的深度学习方法结合使用，旨在克服这些限制中的一些。我们的数据表明，该系统可以准确地分类两个对话者面部不同区域的注视位置，并在（半）自然面对面互动期间捕捉到两个人之间人际注视同步的微妙差异。
