Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures

凝视 计算机视觉 人工智能 跟踪(教育) 眼动 计算机科学 运动(物理) 运动捕捉 匹配移动 心理学 教育学
作者
Rhys Hunt,Tim Blackmore,Chris Mills,Matt Dicks
出处
期刊:I-perception [SAGE]
卷期号:13 (5) 被引量:5
标识
DOI:10.1177/20416695221116652
摘要

Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data collected through the integration. Based on research suggesting increased viewing distances are associated with reduced data quality; the accuracy and precision of gaze data as participants (N = 11) viewed floor-based targets at distances of 1-6 m was investigated. A mean accuracy of 2.55 ± 1.12° was identified, however, accuracy and precision measures (relative to targets) were significantly (p < .05) reduced at greater viewing distances. We then consider if signal processing techniques may improve accuracy and precision, and overcome issues associated with missing data. A 4th-order Butterworth lowpass filter with cut-off frequencies determined via autocorrelation did not significantly improve data quality, however, interpolation via Quintic spline was sufficient to overcome gaps of up to 0.1 s. We conclude the integration of gaze and motion capture presents a viable methodology in the study of human behavior and presents advantages for data collection, treatment, and analysis. We provide considerations for the collection, analysis, and treatment of gaze data that may help inform future methodological decisions.
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