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Quantification of Aesthetic Viewing Using Eye-Tracking Technology:

The Influence of Previous Training in Apparel Design

Juyeon Park

Emily Woods

Colorado State University

Juyeon.Park@colostate.edu

Emily.Woods@rams.colostate.edu

Marilyn DeLong

University of Minnesota

mdelong@umn.edu

Abstract

The purpose of this study is to explore how the viewers’ previous training is related to their aesthetic viewing in various interactions with the form and the context, in relation to apparel design. Ber-lyne’s two types of exploratory behavior, diversive and specific, provided a theoretical framework to this study. Twenty female subjects (mean age=21, SD=1.089) participated. Twenty model images, posed by a male and a female model, were shown on an eye-tracker screen for 10 seconds each. The findings of this study verified Berlyne’s concepts of visual exploration. One of the dif-ferent findings from Berlyne’s theory was that the untrained viewers’ visual attention tended to be more significantly focused on peripheral areas of visual interest, compared to the trained viewers, while there was no significant difference on the central, foremost areas of visual interest between the two groups. The overall aesthetic viewing patterns were also identified. CR Categories: Visual Attention and Eye Movement Control

Keywords: Aesthetic response, apparel design, previous training, eye-tracking technology

1 Introduction

Understanding of aesthetic response is an imperative ability for designers to develop products that appeal to large consumer groups. Particularly in the field of apparel design, the way people dress and evaluate others’ appearances provides fundamental information about contemporary consumers. DeLong [1998] ex-plains that aesthetic response to apparel design is experienced through three different types of interaction that include 1) the form, 2) the viewer, and 3) the context of viewing. The form refers to not only clothing itself, but also how details (e.g., lines, shapes, textures, and colors) relate within the whole. These rela-tionships involve the interaction of the clothing with the body of the wearer (e.g., body proportions, hair colors, skin texture, and color). The viewer is the one who observes the form. A viewer’s response to an aesthetic object is influenced by his or her individ-ual or collective attributes that include age, gender, preference, expectations, values and education. The context indicates the im-mediate physical surrounding and the cultural milieu that impacts viewing.

Given the background, this study, in particular, focuses on how viewers’ educational background affects their aesthetic response to others’ appearance. More specifically, this study aims to ex-plore how the viewers’ previous training is related to their aesthet-ic viewing in various interactions with the form and the context, in relation to apparel design. It has been widely discussed among art and design educators that a more complex aesthetic response can be learned through educa-tion/training. For example, Wilson [1974] asserts that aesthetic education is effective in achieving desirable ends, although evi-dence of effectiveness is hard to materialize. In addition, being aware of the evanescent nature of aesthetic response, namely its tendency of being hidden and bounded within a private realm, DeFurio [1979] argues that aesthetic response can be encouraged within classroom settings. Further, scholars in early childhood education [Acer & Ömeroðlu 2008; Kemple & Johnson 2002] verified the effectiveness of training in nurturing young children’s aesthetic response. Likewise, DeLong [1998] elucidates that edu-cation increases knowledge and the ability to appreciate objects. As noted by previous scholars, although studying aesthetic re-sponse is one of the most challenging and complicated phenome-na in human perception research, eye movement analysis has provided an excellent research tool that has allowed researchers to go beyond speculation. Speaking of the experimental method in aesthetic analysis with a specific interest in training, Solso [1994] uses the example of a radiologist looking at an X-ray; a trained person would know what he or she was looking at and looking for, and an untrained person would have a more erratic, unfocused scan path. Nodine, Locher, and Krupinski [1993] showed a dif-ference between trained and untrained viewers in aspects of art-work that had been manipulated in visual balance. Findings showed that untrained viewers focused primarily on the represen-tational aspects of the image and how well it represented reality, whereas trained viewers focused on elements of the image in terms of symmetry, balance and form. Informed viewing can also affect the scan path of the viewer [Koivunen et al. 2004; Rayner et al. 2001; Yarbus 1967], whereas a viewer given a specific task or information about an image may view it differently.

2 Theoretical Framework

Berlyne’s theory of psychoaesthetics provides a theoretical framework for this study [Berlyne 1971]. The two types of explo-ratory behavior, diversive and specific, are used to explore the differences of the trained and untrained viewers’ aesthetic view-ing patterns. According to Berlyne, diversive exploratory behavior seeks stimulation regardless of content or sources that has appeal-ing qualities or properties, while specific exploration occurs in order to search for further stimulation with a purpose of relieving uncertainty. Widely dispersed, sparsely populated clusters of fixa-tions that typically display short gaze duration are associated with

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diversive exploration. On the other hand, high-densities of fixa-tions and long gaze duration are likely to reflect specific explora-tion. As proposed in a study by Nodine, et al. [1993], this study assumes that the short gaze duration that seeks out attractive, nov-el visual interests, which is diversive exploration (e.g., fixations with less than 300-msec gaze duration), is related to untrained viewers, and the prolonged gaze duration (e.g., fixations with greater than 400-msec gaze durations) that searches meaning and significance to the overall visual image tends to be linked to trained viewers.

Figure 1. Model images used for the experiments

3 Methodology

Twenty female subjects participated in this study. Average age range was 21 (SD=1.089) and the number of art and design-related courses taken was 0-15 (mean=6.4, SD=4.044). Twenty model images that contain four original photos and four manipu-lated photos per original were used for the experiment (Figure 1). Four original photos, posed by a male and a female model, de-picted images with two different ensembles of apparel for each gender. Using computer-aided design (CAD) software, the origi-nal photos were manipulated in accessories, clothing colors, fabric patterns, hair colors, and backgrounds. Each of the images was shown on a 17-inch color eye-tracker (ASL D6) computer screen for 10 seconds. Two questionnaires were administered. Prior to the experiment, participants filled out a questionnaire that asked their background information such as age, gender, comfort level with technology use and familiarity with art/aesthetics/design, and interest in appa-rel shopping. During the actual experiment, a series of twenty images were shown on a computer screen. Immediately after viewing each image, in another questionnaire, the subjects were asked to rate the five categories of visual interests that drew their attention while viewing the image on the computer screen. The categories of possible visual interests were rated, using the 7-point

Likert scale. The categories involved 1) hair/eye color, 2) skin texture/color, 3) clothing color/fabric pattern, 4) image back-ground, and 5) accessories. The total duration of each experiment, including the questionnaire completion and the actual eye-tracking experiments was approximately 20 minutes.

4 Results

Factor analysis was employed to determine the variables that ca-tegorize the subjects’ answers to the questions in the pre-viewing questionnaire. The analysis identified the four background factors that included knowledge (e.g., I consider myself knowledgeable about art and aesthetics), enjoyment (e.g., I like to observe and evaluate others’ appearance), technology (e.g., I am comfortable with using a new technology), and necessity (e.g., I shop clothing based on necessity). In order to determine the relationship be-tween training and the background factors, regression analysis was performed. The number of courses taken (indicator of train-ing) was significantly related to a particular factor, “enjoyment” at 95% confidence level (F=6.111, p=.024). That is, the more courses the subjects have taken, the more they tend to enjoy the circumstances of aesthetic viewing. The different level of training did not show strong relationships with other background factors. In order to determine the relationship between subjective human perception and objective eye-tracking data, the ratings of the five categories in the post-viewing questionnaire and sum of fixation duration (total gaze duration) on each areas of interest (AOI) were compared. For example, in image 1, the subjects rated the catego-ries of the visual interests in the order of clothing color/fabric pattern (n=18, mean=5.28, SD=1.195), hair/eye color (n=12, mean=4.92, SD=1.325), skin (n=8, mean=5.00, SD=1.512), back-ground (n=4, mean=5.75, SD=1.500). For eye-tracking data anal-ysis, the five areas of interest (AOIs) were identified: AOI1 (background), AOI2 (face/hair), AOI3 (clothing), AOI4 (skin), and AOI5 (shoes). Total gaze durations on AOIs were ranked from the longest to the shortest as such: clothing > skin > face/hair > background > shoes. In the particular image (Image 1), although the order of skin and background in eye-tracking data was reversed, compared to the subjects’ ratings in the question-naire, the overall order of the visual interests remained similar. A parallel trend was also found in the rest of the images. This means that the subjects’ self-evaluation on their visual attention was compatible with eye-tracking data.

AOI Description Mean Total Fixation Duration (msec)

Std. Deviation

AOI1 Background 739.2632 725.25588 AOI2 Face/Hair 878.0000 1,037.30942 AOI3 Clothing 1,754.4210 1,533.93702 AOI4 Skin 929.8421 751,32308 AOI5 Shoes 61.4737 84.72529

Figure 2. Total Fixation Duration of AOIs in Image 1

Regression analysis was used to find the relationship between the subjects’ training level and their aesthetic viewing patterns. When a model with fewer visual interests was presented on a plain background such as Image 2 (Figure 2), the more trained the sub-ject was, the lower interfixation distance, that is, the more densi-ties of fixations were found in AOI1 (background). That is, when a simple context was given, the trained group tends to examine the wider areas on the image. On the other hand, the peripheral areas such as shoes (AOI5) showed a significant difference be-tween the trained and untrained group: the less trained, the more

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fixations and the longer scanning time (F=6.993, p=.016) around the shoes area. This means that when the image is more compli-cated, while the trained group tends to scan the entire image, the untrained group tends to look at particular areas. The same pattern is also found on the images with a male model. For instance in image 19 (refer to Figure 1), with the male model image wearing a shirt with a complex pattern appearing on a complicated street background, significantly more fixations were found on the shirt among the untrained, in comparison with the trained group (F=4.116, p=0.38). In this study we also discovered several key findings in overall viewing patterns: 1) if an image contains visual interest on the model's clothing, the viewer is likely to look at the clothing first and then move to the face. 2) If an image has more complexity on the background, the viewer's viewing path tends to encompass wider areas on the image, because of the viewer's continuous eye movements to identify the relationship between the model and the background. 3) With a background of low visual interest, the viewer's immediate attention goes to the areas of contrast with the background first and then scans of the model up and down. 4) Regardless of relationships that an image envisages among the body, clothing and background, the overall path of aesthetic view-ing on standing human models shows a vertical direction.

Figure 3. Image 2: An untrained viewer’s scan path (left) and a

trained viewer’s scan path (right)

5 Conclusion

The findings of this study are that the untrained viewers focused more on areas of visual stimulation rather than on the relation-ships among the elements in the image. This verifies Berlyne’s concepts of diversive and specific exploration. One of the differ-ences from Berlyne’s theory was that the untrained viewers’ visu-al attention tended to be significantly more focused on peripheral areas of visual interest, compared to the trained viewers, while

there was no significant difference on the central, foremost areas of visual interest between the two groups. On the other hand, the trained viewers’ interfixation duration, namely scanning time, was much longer than the untrained viewers, which indicates that the trained viewers spend more time exploring the relationships among the design elements on the image. The overall aesthetic viewing pattern suggests that in aesthetic viewing, people tend to examine others' appearance largely in a vertical direction, while involving various sub-paths of viewing to discern the relation-ships of the forms. These findings imply that aesthetic training for apparel design students is highly desirable, in order not just to teach them to appreciate others’ appearances in a systematic way, but more importantly to design products that can maximize con-sumers’ satisfaction by comprehending their diverse needs in the ever-competitive apparel manufacturing market.

6 References

ACER, D., & ÖMEROÐLU, E. 2008. A Study on the effect of aesthetic education on the development of aesthetic judg-ment of six-year-old children. Early Childhood Education

Journal, 35, 4, 1573-1707. BERLYNE, D.E. 1971. Aesthetics and psychobiology. New York:

Appleton-Century- Crofts. DEFURIO, A. G. 1979. Toward aesthetic response. Art Educa-

tion, 32,7, 8-11. DELONG, M.R. 1998. The way we look. (2nd Ed.). New York:

Fairchild Publications. KEMPLE, K., & JOHNSON, C. 2002. From the inside out: Nur-

turing aesthetic response to nature in the primary grades. Childhood Education, 78, 4, 210-218.

KOIVUNEN, K., KUKKONEN, S., LAHTINEN, S., RANTALA, H., AND SHARMIN, S. 2004. Towards deeper under-standing of how people perceive design in products. In M. Agger Eriksen, L. Malmbord, and J. Nielsen (Eds.) Pro-ceedings of Computers in Art and Design Education

CADE2004, Copenhagen Business School, Denmark & Malmö University, Sweden.

NODINE, C.F., LOCHER, P.J., & KRUPINSKI, E.A. 1993. The role of formal art training on perception and aesthetic judgement of art compositions. Leonardo, 26, 219-227.

RAYNER, K., ROTELLO, C.M., STEWART, A.J., KEIR, J., & DUFFY, S.A. 2001. Integrating text and pictorial infor-mation: Eye movements when looking at print advertise-ments. Journal of Experimental Psychology: Applied, 7, 3, 219-226.

SOLSO, R.L. 1994. Cognition and the visual Arts. Cambridge, Massachusetts: MIT Press.

WILSON, B. 1974. One view of the past and future of research in aesthetic education. Journal of Aesthetic Education, 8, 3, 59-67.

YARBUS, A.L. 1967. Eye movements and vision. New York: Plenum Press.

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