Potsdam Eye-Movement Corpus for Scene Memorization and Search with Color and Spatial-Frequency Filtering

The availability of large eye-movement corpora has become increasingly important over the past years. In scene viewing, scan-path analyses of time-ordered fixations, for example, allow for investigating individual differences in spatial correlations between fixation locations, or for predicting individual viewing behavior in the context of computational models. However, time-dependent analyses require many fixations per scene, and only few large eye-movement corpora are publicly available. This manuscript presents a new corpus with eye-movement data from two hundred participants. Viewers memorized or searched either color or grayscale scenes while high or low spatial frequencies were filtered in central or peripheral vision. Our database provides the scenes from the experiment with corresponding object annotations, preprocessed eye-movement data, and heatmaps and fixation clusters based on empirical fixation locations. Besides time-dependent analyses, the corpus data allow for investigating questions that have received little attention in scene-viewing research so far: (i) eye-movement behavior under different task instructions, (ii) the importance of color and spatial frequencies when performing these tasks, and (iii) the individual roles and interaction of central and peripheral vision during scene viewing. Furthermore, the corpus allows for validation of computational models of attention and eye-movement control, and finally, analyses on an object- or cluster-based level.

Eye Movements during dynamic scene viewing are affected by visual attention skills and events of the scene: Evidence from first-person shooter gameplay videos

The role of individual differences during dynamic scene viewing was explored. Participants (N=38) watched a gameplay video of a first-person shooter (FPS) videogame while their eye movements were recorded. In addition, the participants’ skills in three visual attention tasks (attentional blink, visual search, and multiple object tracking) were assessed. The results showed that individual differences in visual attention tasks were associated with eye movement patterns observed during viewing of the gameplay video. The differences were noted in four eye movement measures: number of fixations, fixation durations, saccade amplitudes and fixation distances from the center of the screen. The individual differences showed during specific events of the video as well as during the video as a whole. The results highlight that an unedited, fast-paced and cluttered dynamic scene can bring about individual differences in dynamic scene viewing.

A Computational Dual-Process Model of Fixation-Duration Control in Natural Scene Viewing

Research on eye-movement control during natural scene viewing has investigated the degree to which the duration of individual fixations can be immediately adjusted to ongoing visual-cognitive processing demands. Results from several studies using the fixation-contingent scene quality paradigm suggest that the timing of fixations adapts to stimulus changes that occur on a fixation-to-fixation basis. Analysis of fixation-duration distributions has revealed that saccade-contingent degradations and enhancements of the scene stimulus have two qualitatively distinct types of influence. The surprise effect begins early in a fixation and is tied to surprising visual events such as unexpected stimulus changes. The encoding effect is tied to difficulties in visual-cognitive processing and occurs relatively late within a fixation. Here, we formalize an existing descriptive account of these two effects (referred to as the dual-process account) by using stochastic simulations. In the computational model, surprise and encoding related influences are implemented as time-dependent changes in the rate at which saccade timing and programming are completed during critical fixations. The model was tested on data from two experiments in which the luminance of the scene image was either decreased or increased during selected critical fixations (Walshe & Nuthmann, Vision Research, 100, 38–46 2014). A counterfactual method was used to remove model components and to identify their specific influence on the fixation_duration distributions. The results suggest that the computational dual-process model provides a good account for the data from the luminance-change studies. We describe how the simulations can be generalized to explain a diverse set of experimental results.

Objects are Prioritized for Attention Based Upon Meaning During Active Scene Viewing

Although the physical salience of objects has previously been demonstrated to guide attention in real-world scene perception, it is unknown whether objects are also prioritized based on their meaning. To answer this question, we computed the average meaning and the average physical salience of objects in scenes. Using eye movement data from aesthetic judgment and memorization tasks, we then tested whether fixations are more likely to land on high-meaning objects than low-meaning objects while controlling for object salience. The results demonstrated that fixations are more likely to be directed to high meaning objects than low meaning objects regardless of object salience. Furthermore, the influence of object salience was progressively reduced as object meaning increased and was eliminated at the highest levels of meaning. Overall, these findings provide the first evidence that objects are prioritized by meaning for attentional selection during active scene viewing.

The interplay between gaze and consistency in scene viewing: Evidence from visual search by young and older adults

Searching for an object in a complex scene is influenced by high-level factors such as how much the item would be expected in that setting (semantic consistency). There is also evidence that a person gazing at an object directs our attention towards it. However, there has been little previous research that has helped to understand how we integrate top-down cues such as semantic consistency and gaze to direct attention when searching for an object. Also, there are separate lines of evidence to suggest that older adults may be more influenced by semantic factors and less by gaze cues compared to younger counterparts, but this has not been investigated before in an integrated task. In the current study we analysed eye-movements of 34 younger and 30 older adults as they searched for a target object in complex visual scenes. Younger adults were influenced by semantic consistency in their attention to objects, but were more influenced by gaze cues. In contrast, older adults were more guided by semantic consistency in directing their attention, and showed less influence from gaze cues. These age differences in use of high-level cues were apparent early in processing (time to first fixation and probability of immediate fixation) but not in later processing (total time looking at objects and time to make a response). Overall, this pattern of findings indicates that people are influenced by both social cues and prior expectations when processing a complex scene, and the relative importance of these factors depends on age.