Gist Perception of Image Composition in Abstract Artworks

Abstract

Most recent studies in experimental aesthetics have focused on the cognitive processing of visual artworks. In contrast, the perception of formal compositional features of artworks has been studied less extensively. Here, we investigated whether fast and automatic processing of artistic image composition can lead to a stable and consistent aesthetic evaluation when cognitive processing is minimized or absent. To this aim, we compared aesthetic ratings on abstract artworks and their shuffled counterparts in a gist experiment. Results show that exposure times as short as 50 ms suffice for the participants to reach a stable and consistent rating on how ordered and harmonious the abstract stimuli were. Moreover, the rating scores for the 50 ms exposure time exhibited similar dependencies on image type and self-similarity and a similar pattern of correlations between different rating terms, as the rating scores for the long exposure time (3,000 ms). Ratings were less consistent for the term interesting and inconsistent for the term pleasing. Our results are compatible with a model of aesthetic experience, in which the early perceptual processing of the formal aspects of visual artworks can lead to a consistent aesthetic judgment, even if there is no cognitive contribution to this judgment.

Tracking two pleasures

“…Thus, the two images were at symmetric eccentricities in the left and right periphery of the observer's vision, avoiding greater attention to one image closer to the center of fixation. Subjectively felt pleasure from an image is reported reliably after presentation durations as short as 50 ms (e.g., Brielmann & Pelli, 2018;Forster, Leder, & Ansorge, 2016;Schwabe, Menzel, Mullin, Wagemans, & Redies, 2018).…”

Global Image Properties Predict Ratings of Affective Pictures

“…Grebenkina et al (2018) reported predicted variances between 5% (for pleasing ratings of CD album covers) and 55% (for liking ratings of building facade photographs). Schwabe et al (2018) analyzed abstract artworks and non-artistic images and obtained predicted variances that ranged from 27 to 46% for ratings of how harmonious and ordered the images were, respectively. The variances predicted in the present study are thus comparatively low to moderate (up to 20%), depending on the dataset analyzed.…”

“…However, physical image properties that represent lowlevel perceptual features can also have an effect on emotional processing (Delplanque et al, 2007;Satpute et al, 2015). The human visual system processes low-level features fast and automatically, allowing humans to recognize not only the general meaning of scenes (Oliva and Torralba, 2006) at a glance ("gist perception, " Bachmann and Vipper, 1983), but also to evaluate affective aspects of images, such as their esthetic value (Cupchik and Berlyne, 1979;Mullin et al, 2017;Verhavert et al, 2017;Schwabe et al, 2018). Examples of low-level features studied in affective pictures are image brightness (Lakens et al, 2013;Kurt et al, 2017), color (Bekhtereva and Muller, 2017) and spatial frequency content (Delplanque et al, 2007;De Cesarei and Codispoti, 2013;Muller and Gundlach, 2017).…”

Comparison of Outlier-Tolerant Models for Measuring Visual Complexity

“…Some works such as Forsythe’s [ 26 ] and Marin’s [ 5 ] showed that methods such as Canny or Perimeter Detection, based on phase congruence, are also optimal for measuring visual complexity. Other studies on experimental aesthetics published recently have focused on investigating how the exposure time of the stimulus affects image processing [ 31 ]. To do this, the intrinsic and extrinsic factors that affect the human response on the aesthetic value of the images were examined [ 32 ], as well as the way in which the “good composition” or the “visual rightness” is revealed according with edge orientation and luminance [ 33 ].…”