TL;DR
The paper introduces the gaze spiral visualization technique for mobile eye tracking data, enabling compact, overview-rich representations of scanpaths that facilitate comparison and pattern recognition without manual annotation.
Contribution
It presents a novel gaze spiral visualization method that aligns eye tracking data with image content, improving analysis of long-term, multi-participant recordings.
Findings
Effective visualization of long-term eye tracking data
Facilitates comparison of multiple recordings
Helps identify recurring viewing patterns
Abstract
Comparing mobile eye tracking data from multiple participants without information about areas of interest (AOIs) is challenging because of individual timing and coordinate systems. We present a technique, the gaze spiral, that visualizes individual recordings based on image content of the stimulus. The spiral layout of the slitscan visualization is used to create a compact representation of scanpaths. The visualization provides an overview of multiple recordings even for long time spans and helps identify and annotate recurring patterns within recordings. The gaze spirals can also serve as glyphs that can be projected to 2D space based on established scanpath metrics in order to interpret the metrics and identify groups of similar viewing behavior. We present examples based on two egocentric datasets to demonstrate the effectiveness of our approach for annotation and comparison tasks.…
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