Individual fixation tendencies in person viewing generalize from images to videos

Abstract

Fixation behavior toward persons in static scenes varies considerably between individuals. However, it is unclear whether these differences generalize to dynamic stimuli. Here, we examined individual differences in the distribution of gaze across seven person features (i.e. body and face parts) in static and dynamic scenes. Forty-four participants freely viewed 700 complex static scenes followed by eight director-cut videos (28,925 frames). We determined the presence of person features using hand-delineated pixel masks (images) and Deep Neural Networks (videos). Results replicated highly consistent individual differences in fixation tendencies for all person features in static scenes and revealed that these tendencies generalize to videos. Individual fixation behavior for both, images and videos, fell into two anticorrelated clusters representing the tendency to fixate faces versus bodies. These results corroborate a low-dimensional space for individual gaze biases toward persons and show they generalize from images to videos.

Keywords: eye movements; face perception; individual differences; objects and features; scene perception.

Figure 1.

Split-half consistencies and interfeature correlations (images). Correlation matrices in (a, b) show the covariance between fixation tendencies in off-diagonal cells and their split-half consistencies on the diagonal for (a) proportions of first fixations and (b) proportional dwell times. Negative to positive correlations are indicated by color and saturation, as shown on the color bar to the right. Asterisks indicate statistical significance (Holm–Bonferroni corrected for multiple testing) **p < .001, *p < .05. (c, d) show the corresponding two-dimensional projections derived with multidimensional scaling.

Figure 2.

Head versus body fixations across all fixations. The figure shows the scatter plots for the negative correlation between the features head and body across all fixations (not just those landing on persons). Each scatter point represents the proportion of fixations of a single observer, which landed on the respective feature for (a) proportions of first fixations, (b) proportional dwell time, and (c) the proportion of video gaze samples. The least-square lines are shown in black and corresponding correlation values are written in the top right of each plot.

Figure 3.

Split-half consistencies and interfeature correlations (videos). The correlation matrix in (a) shows the covariance between gaze tendencies in off-diagonal cells and their split-half consistencies on the diagonal for proportions of video fixations. (b) shows the corresponding two-dimensional projection derived with multidimensional scaling. (c) shows the correlations between the proportion of video gaze samples and the proportion of first fixation (green) or proportional dwell time (grey) in images, respectively, for all features. Asterisks indicate statistical significance (Holm–Bonferroni corrected for multiple testing) **p < .001, *p < .05.