Abstract Analyses of human gaze behaviour towards complex scenes typically aim to explain heatmaps or scan-paths. While heatmaps lack temporal information, scan-paths aim for a level of detail which often is impractical. We introduce a novel approach, based on the premise that most fixations target objects and do so in meaningfully different ways, depending on temporal context: Detection fixations (D) foveate an object for the first time; Inspection fixations (I) successively target object details; and Return fixations (R) revisit a previously fixated object after going elsewhere. To test the hypothesis that these classes capture distinct fixation profiles, we reanalysed a large dataset of scene fixations. We computed separate heatmaps for D, I, and R and found significantly higher inter-o…

DISCUSSION Traditional models of visual attention either focus on the spatial distribution of fixations across an image (e.g., heatmaps) or on their precise sequence in scan-paths. However, neither approach utilizes the object-directed nature of typical fixation sequences, nor allows for intuitive distinctions between different types of fixations. Here, we present a simple algorithm to sort fixations towards naturalistic scenes into three distinct classes. An evaluation on a large scene viewing dataset confirmed systematic and reliable differences between Detections, Inspections and Returns, including distinct salience profiles and dynamics. We computed separate D, I, and R fixation maps for 700 naturalistic scenes using data from >100 observers and found reliable differences between these classes, which generalised across images and observers. Previous work has shown a shift in fixation duration and saccadic amplitude over free viewing time (ambient vs. focal mode; Pannasch et al.,; Unema et al.,) and examined the proportion of refixations under different task instructions and visuo-sensorimotor tasks (e.g., Droll & Hayhoe,). The algorithm proposed here classifies each object-dire…

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