What we look at in paintings: A comparison between experienced and inexperienced art viewers

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought of as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, and compare the eye movements of experienced and inexperienced art viewers. In addition, we develop a stochastic model, which is rather simple but fits quite well to the eye movement data, to further investigate the differences between the two groups through functional summary statistics

An Application of Deep-Learning to Understand Human Perception of Art

Eye movement patterns are known to differ when looking at stimuli given a different task, but less is known about how these patterns change as a function of expertise. When a particular visual pattern is viewed, a particular sequence of eye movements are executed and this sequence is defined as scanpath. In this work we made an attempt to answer the question, “Do art novices and experts look at paintings differently?” If they do, we should be able to discriminate between the two groups using machine learning applied to their scanpaths. This can be done using algorithms for Multi-Fixation Pattern Analyses (MFPA). MFPA is a family of machine learning algorithms for making inferences about people from their gaze patterns. MFPA and related approaches have been widely used to study viewing behavior while performing visual tasks, but earlier approaches only used gaze position (x, y) information with duration and temporal order and not the actual visual features in the image. In this work, we extend MFPA algorithms to use visual features in trying to answer a question that has been overlooked by most early studies, i.e. if there is a difference found between experts and novices, how different are their viewing patterns and do these differences exist for both low- and high-level image features. To address this, we combined MFPA with a deep Convolutional Neural Network (CNN). Instead of converting a trial’s 2-D fixation positions into Fisher Vectors, we extracted image features surrounding the fixations using a deep CNN and turn them into Fisher Vectors for a trial. The Fisher Vector is an image representation obtained by pooling local image features. It is frequently used as a global image descriptor in visual classification. We call this approach MFPA-CNN. While CNNs have been previously used to recognize and classify objects from paintings, this work goes the extra step to study human perception of paintings. Ours is the first attempt to use MFPA and CNNs to study the viewing patterns of the subjects in the field of art. If our approach is successful in differentiating novices from experts with and without instructions when both low- and high-level CNN image features were used, we could then demonstrate that novices and experts view art differently. The outcome of this study could be then used to further investigate what image features the subjects are concentrating on. We expect this work to influence further research in image perception and experimental aesthetics

The Influence of Pupil Alignment on Spectator Address in Manet's Portraiture

Participants judged 94 portraits painted by Édouard Manet (70), Gustave Courbet (12) and Henri Fantin-Latour (12) for horizontal and vertical pupil misalignment and gaze ambiguity (Experiment 1) and focal point of gaze (Experiment 2). Eye movements were also measured as participants considered the extent to which sitters in the same portraits acknowledged viewers (spectators; Experiment 3). The results showed Manet portraits to be frequently painted with misaligned pupils that are associated with gaze ambiguity, especially when misaligned on the vertical axis. This ambiguity of gaze was associated with the average focal point of gaze as being judged further up and to the left of the centre for ambiguous relative to non-ambiguous portraits. These decisions in relation to portraits displaying ambiguous gaze were associated with increased eye-movements to the eye region relative to those portraits not displaying ambiguity. Finally, ratings of acknowledgement taken in Experiment 3 correlated with those of gaze ambiguity taken in Experiment 1. The results are interpreted in terms of the role of eye gaze in influencing spectatorship of portraits and, specifically, Fried’s theory of the ‘double relation’ (Fried 1980; Fried 1996) between painting and spectator in the paintings of Manet

Identifying experts in the field of visual arts using oculomotor signals

In this article, we aimed to present a system that enables identifying experts in the field of visual art based on oculographic data. The difference between the two classified groups of tested people concerns formal education. At first, regions of interest (ROI) were determined based on position of fixations on the viewed picture. For each ROI, a set of features (the number of fixations and their durations) was calculated that enabled distinguishing professionals from laymen. The developed system was tested for several dozen of users. We used k-nearest neighbors (k-NN) and support vector machine (SVM) classifiers for classification process. Classification results proved that it is possible to distinguish experts from non-experts

Reappraising Abstract Paintings after Exposure to Background Information

Can knowledge help viewers when they appreciate an artwork? Experts’ judgments of the aesthetic value of a painting often differ from the estimates of naïve viewers, and this phenomenon is especially pronounced in the aesthetic judgment of abstract paintings. We compared the changes in aesthetic judgments of naïve viewers while they were progressively exposed to five pieces of background information. The participants were asked to report their aesthetic judgments of a given painting after each piece of information was presented. We found that commentaries by the artist and a critic significantly increased the subjective aesthetic ratings. Does knowledge enable experts to attend to the visual features in a painting and to link it to the evaluative conventions, thus potentially causing different aesthetic judgments? To investigate whether a specific pattern of attention is essential for the knowledge-based appreciation, we tracked the eye movements of subjects while viewing a painting with a commentary by the artist and with a commentary by a critic. We observed that critics’ commentaries directed the viewers’ attention to the visual components that were highly relevant to the presented commentary. However, attention to specific features of a painting was not necessary for increasing the subjective aesthetic judgment when the artists’ commentary was presented. Our results suggest that at least two different cognitive mechanisms may be involved in knowledge-guided aesthetic judgments while viewers reappraise a painting

Meeting Eye To Eye : How Trained Designers And Typical Viewers See Design Pieces : And Their Implications For Contemporary Design Education

This study investigated and compared gaze patterns of typical viewers and trained designers to learn if there are differences in the gaze patterns between the two groups. Using eye tracking technology, participants were asked to interpret orally and in writing the effectiveness of the compositions of several advertisements and a company letterhead. The research data included the recorded gaze patterns of participants and the oral and written remarks of the viewers. The questions asked the participants to assess their responses to and appreciation of the compositions. This study shows that similar elements of design are of importance to experts and novices alike, but that experts viewed the art differently than novices.  M.A.Ed

Assessment of Visual Literacy – Contributions of Eye Tracking

Visual Literacy (VL) is defined as a set of competencies to understand and express oneself through visual imagery. An expansive model, the Common European Framework of Reference for Visual Literacy (CEFR-VL) (Wagner & Schönau, 2016), comprises 16 sub-competencies, including abilities such as analyzing, judging, experimenting with or aesthetically experiencing images. To empirically assess VL sub-competencies different visual tasks were presented to VL experts and novices. Problem-solving behavior and cognitive strategies involved in visual logical reasoning (Paper 1), Visual Search (Paper 2), and judgments of visual abstraction (Paper 3) were investigated. Eye tracking in combination with innovative statistical methods were used to uncover latent variables during task performance and to assess the possible effects of differences in expertise level. Furthermore, the relationship between students' self-reported visual abilities and their performance on VL assessment tasks is systematically explored. Results show how effects of perceptual skills of VL experts are less pronounced and more nuanced than implied by VL models. The comprehension of visual logical models does not seem to depend much on VL, as experts and novices did not differ in their solution strategies and eye movement indicators (Paper 1). In contrast, the visual search task on artworks revealed how experts were able to detect target regions with higher efficiency than novices revealed by higher precision of fixations on target regions. Furthermore, latent image features were detected by experts with more certainty (Paper 2). The assessment of perceived level of visual abstraction revealed how, contrary to our expectations, experts did not outperform novices but despite that were able to detect nuanced level of abstraction compared to student groups. Distribution of fixations indicate how attention is directed towards more ambiguous images (Paper 3). Students can be classified based on different levels of visual logical comprehension (Paper 1), on self-reported visual skills, and the time spent on the tasks (Paper 2, Paper 3). Self-reported visual art abilities of students (e.g., imagination) influences the visual search and the judgment of visual abstraction. Taken together the results show how VL skills are not determined solely by the number of correct responses, but rather by how visual tasks are solved and deconstructed; for example, experts are able to focus on less salient image regions during visual search and demonstrate a more nuanced interpretation of visual abstraction. Low-level perceptual abilities of experts and novices differ marginally, which is consistent with research on art expertise. Assessment of VL remains challenging, but new empirical methods are proposed to uncover the underlying components of VL

Professional Development in Sculpture

This dissertation discusses the process involved sculptors becoming professionals and the aspects that characterise a professional sculptor when compared to art students

Assessing Heterogeneity in Students’ Visual Judgment: Model-Based Partitioning of Image Rankings

Differences in the ability of students to judge images can be assessed by analyzing the individual preference order (ranking) of images. To gain insights into potential heterogeneity in judgement of visual abstraction among students, we combine Bradley–Terry preference modeling and model-based recursive partitioning. In an experiment a sample of 1,020 high-school students ranked five sets of images, three of which with respect to their level of visual abstraction. Additionally, 24 art experts and 25 novices were given the same task, while their eye movements were recorded. Results show that time spent on the task, the students’ age, and self-reported interest in visual puzzles had significant influence on rankings. Fixation time of experts and novices revealed that both groups paid more attention to ambiguous images. The presented approach makes the underlying latent scale of visual judgments quantifiable