Personality, Psychological Assessment, and Psychological Methods, University of Koblenz-Landau, Fortstr. 7, 76829, Landau, Germany.
Abteilung für Angewandte Psychologie und Methodenforschung, Alpen-Adria-Universität Klagenfurt, Universitätsstraße 65-67, 9020, Klagenfurt am Wörthersee, Austria.
Behav Res Methods. 2019 Apr;51(2):747-768. doi: 10.3758/s13428-018-1085-9.
This article proposes an optical measurement of movement applied to data from video recordings of facial expressions of emotion. The approach offers a way to capture motion adapted from the film industry in which markers placed on the skin of the face can be tracked with a pattern-matching algorithm. The method records and postprocesses raw facial movement data (coordinates per frame) of distinctly placed markers and is intended for use in facial expression research (e.g., microexpressions) in laboratory settings. Due to the explicit use of specifically placed, artificial markers, the procedure offers the simultaneous measurement of several emotionally relevant markers in a (psychometrically) objective and artifact-free way, even for facial regions without natural landmarks (e.g., the cheeks). In addition, the proposed procedure is fully based on open-source software and is transparent at every step of data processing. Two worked examples demonstrate the practicability of the proposed procedure: In Study 1(N= 39), the participants were instructed to show the emotions happiness, sadness, disgust, and anger, and in Study 2 (N= 113), they were asked to present both a neutral face and the emotions happiness, disgust, and fear. Study 2 involved the simultaneous tracking of 14 markers for approximately 12 min per participant with a time resolution of 33 ms. The measured facial movements corresponded closely to the assumptions of established measurement instruments (EMFACS, FACSAID, Friesen & Ekman, 1983; Ekman & Hager, 2002). In addition, the measurement was found to be very precise with sub-second, sub-pixel, and sub-millimeter accuracy.
本文提出了一种应用于情感面部表情视频记录的运动光学测量方法。该方法提供了一种从电影行业中获取运动的方式，在电影行业中，可以使用模式匹配算法来跟踪放置在皮肤表面的标记。该方法记录和后处理原始的面部运动数据（每帧的坐标），并明确放置的标记，旨在用于实验室环境中的面部表情研究（例如微表情）。由于明确使用了特别放置的人工标记，该程序可以以（心理测量学）客观且无伪影的方式同时测量多个与情绪相关的标记，即使对于没有自然标记（例如脸颊）的面部区域也是如此。此外，所提出的程序完全基于开源软件，并且在数据处理的每个步骤都是透明的。两个示例研究说明了所提出的程序的实用性：在研究 1（N=39）中，要求参与者展示快乐、悲伤、厌恶和愤怒这四种情绪；在研究 2（N=113）中，他们被要求展示中性脸以及快乐、厌恶和恐惧这四种情绪。研究 2涉及对每个参与者的大约 12 分钟进行 14 个标记的同时跟踪，时间分辨率为 33ms。所测量的面部运动与既定测量仪器（EMFACS、FACSAID、Friesen 和 Ekman，1983；Ekman 和 Hager，2002）的假设非常吻合。此外，该测量具有亚秒、亚像素和亚毫米级的精度，非常精确。
