Track 05 – Analysis and Interpretation

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https://diglib.eg.org/handle/10.2312/3607222

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Browsing Track 05 – Analysis and Interpretation by Subject "Applied computing → Archaeology"

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    Acting Like an Expert: Analyzing Eye and Movement Behavior when Exploring Archaeological Artifacts
    (The Eurographics Association, 2025) Dumonteil, Maxime; Nicolas, Théophane; Macé, Marc J.-M.; Gouranton, Valérie; Leguedois, Yan; Gaugne, Ronan; Campana, Stefano; Ferdani, Daniele; Graf, Holger; Guidi, Gabriele; Hegarty, Zackary; Pescarin, Sofia; Remondino, Fabio
    This study proposes a novel methodological framework for investigating the visual exploration of archaeological artifacts in both real and virtual environments, integrating eye-tracking and movement data to analyze user behavior. Focused on three vases of varying shapes and decorative registers, the research examines the influence of object characteristics and user expertise on exploration strategies. Our results reveal that while both expert and non-expert participants identify structural and diagnostic features, such as geometric patterns and manufacturing traces, experts engage in more integrative, analytical exploration, focusing on both technical and decorative aspects. In contrast, non-experts prioritize prominent visual cues, often without full comprehension of their significance. These findings demonstrate that visual behaviors are influenced both by the physical characteristics of the artifacts and by the observer's level of expertise. They also show that certain visual cues--such as shape transitions or manufacturing marks--are particularly effective in triggering recognition, even among non-experts. This study contributes to neuro-archaeology by advancing eye-tracking and users' movements analysis as tools for analyzing cognitive processes in archaeological interpretation, offering a robust, reproducible methodology that can be applied to diverse archaeological contexts, enhancing our understanding of how artifacts reveal archaeologically meaningful information through visual perception.