Gaze Data Analysis

Abstract

Analysis of gaze data collected during experiments is an essential part of any study that deals with eye tracking. In turn, analysis of gaze data is not a trivial procedure, on account of the nature of eye movement, peculiarities of human vision, and the imperfection of the measurement tools. In this chapter, we first draw out the most common issues that researchers are trying to resolve for analysis of gaze data, then present in detail the well-known methods and procedures of gaze data analysis, and finally point to the latest achievements in this field. The chapter contains a specification of the most promising directions in this field of research. We finish with a brief description of the most well-known academic and commercial tools that have been developed for gaze data visualisation and analysis. This chapter is based on an updated version of work originally published by Špakov in 2008.

Assessment of User Preferences for In-Car Display Combinations during Non-Driving Tasks: An Experimental Study Using a Virtual Reality Head-Mounted Display Prototype

“…While capturing accurate data, the data are also converted into a heatmap. The specific formula is expressed in Appendix C, where the gaze duration relative to the total time (percentage) corresponds to colors; then, through color mapping such as "red green blue", areas with more concentrated and longer gaze durations are shown in warm colors (such as red), whereas the opposite areas are shown in cool colors [40]. Regarding data analysis, the obtained visual attention mapping data are analyzed using range analysis of orthogonal experiments.…”

OnMapGaze and GraphGazeD: A Gaze Dataset and a Graph-Based Metric for Modeling Visual Perception Differences in Cartographic Backgrounds Used in Online Map Services

“…Such visualizations highlight the allocation of visual attention during the observation of visual stimuli, thereby aiding in qualitative examination and providing a comprehensive overview of scanning behavior. Among the performed visualization methods, heatmaps provide a clearer representation of eye movement data spatial distribution [45]. This method is applicable to both static and dynamic stimuli and can be implemented either post-experimentally or in real-time applications (e.g., [46]).…”

A-DisETrac Advanced Analytic Dashboard for Distributed Eye Tracking

“…Existing eye movement analysis tools primarily visualize data through heat maps, gaze plots, AOI plots, dynamic pupil diameter/gaze plots, and main sequence plots. Among these, heat maps (attention maps), perception maps (gaze opacity maps), and gaze plots (scanpaths) are often used to visualize spatio-temporal relationships in gaze data (Drusch et al 2014;Špakov et al 2007). Likewise, statistical graphs, such as mean fixation duration, mean saccade amplitude, and mean saccade velocity, are often used to summarize gaze data across time (Berg et al 2009;Convertino et al 2003;Smith et al 2013).…”