Stein Isabell, Jossberger Helen, Gruber Hans
University of Regensburg, Germany.
University of Turku, Finland.
J Eye Mov Res. 2023 May 31;15(3). doi: 10.16910/jemr.15.3.8. eCollection 2022.
Mobile eye tracking helps to investigate real-world settings, in which participants can move freely. This enhances the studies' ecological validity but poses challenges for the analysis. Often, the 3D stimulus is reduced to a 2D image (reference view) and the fixations are manually mapped to this 2D image. This leads to a loss of information about the three-dimensionality of the stimulus. Using several reference images, from different perspectives, poses new problems, in particular concerning the mapping of fixations in the transition areas between two reference views. A newly developed approach (MAP3D) is presented that enables generating a 3D model and automatic mapping of fixations to this virtual 3D model of the stimulus. This avoids problems with the reduction to a 2D reference image and with transitions between images. The x, y and z coordinates of the fixations are available as a point cloud and as .csv output. First exploratory application and evaluation tests are promising: MAP3D offers innovative ways of post-hoc mapping fixation data on 3D stimuli with open-source software and thus provides cost-efficient new avenues for research.
移动眼动追踪有助于研究参与者可以自由移动的现实世界场景。这提高了研究的生态效度，但给分析带来了挑战。通常，三维刺激会被简化为二维图像（参考视图），注视点会被手动映射到这个二维图像上。这导致了关于刺激三维性的信息丢失。使用来自不同视角的多个参考图像会带来新的问题，特别是在两个参考视图之间的过渡区域中注视点的映射问题。本文提出了一种新开发的方法（MAP3D），该方法能够生成三维模型并将注视点自动映射到刺激的这个虚拟三维模型上。这避免了简化为二维参考图像以及图像之间过渡的问题。注视点的x、y和z坐标可以作为点云以及.csv输出文件获取。初步的探索性应用和评估测试很有前景：MAP3D提供了使用开源软件在三维刺激上进行事后映射注视点数据的创新方法，从而为研究提供了经济高效的新途径。
