Practice and Perception in Art & Design
If you look around now, you will probably see mostly plain and simple areas (such as a clear sky or plain walls), whilst there might be regular patterns in smaller areas (clothing and furnishings) and perhaps also some irregular patterns (carpet, grass or clouds). Besides anything living (people, pets and plants), the most complex visual things around are probably objects of aesthetic value. Why artworks tend to be complex, and how visual complexity relates to aesthetic value, are the questions answered in this research.
This PhD was undertaken in the School of Art & Design at Nottingham Trent University, UK, from 2006—2010. The examiner was Linda Candy of the University of Technology, Sydney. The supervisory team at NTU comprised:
- Prof. Judith Mottram, Dean of the School of Art & Design; Professor of Visual Art
- Prof. Terry Shave, Academic Team Leader, Visual Arts
- Dr. Andrew Dunn, Senior Lecturer in Psychology
This research investigates the aesthetics of visual complexity in the practice and perception of visual art and design. The aim is to understand visual complexity in terms of the relationship between the objective properties of images and subjective properties of perception. I take a computational and empirical approach to this subject, incorporating methods from information theory, computer graphics, complexity theory and experimental psychology. For testing, I create cellular automata programs to generate stimulus images, and borrow a variety of visual material from students and professional artists, designers and craftspeople. Visual complexity is measured in two ways: Firstly, an objective measure of complexity is based on the data compression of digital image files, which provides an information-based scale of order to randomness. Secondly, psychophysical techniques are employed to measure the perceived complexity of the images and judgements of preference and artistic quality. Research in complex systems theory and empirical aesthetics suggests that we can expect to find an inverted ‘U’ correlation between the two measures of complexity.
The project makes an original contribution to knowledge with empirical evidence for the inverted ‘U’ correlation of image file compression and perceived complexity. With cellular automata images from simple to complex, the two measures show a correlation which diverges as images approach randomness. The results are less clear with art and design images, however, perhaps due to the wider variety of visual material. The correlation between file compression and perception suggests that we can understand visual complexity as a mixture of order and chaos. A balance of complexity allows for visual exploration and pattern-finding which contributes to aesthetic value. Preference is more variable than judgements of complexity, and art-trained participants rated images higher than untrained participants. The perception of complexity is shown to be more strongly correlated with judgements of artistic quality than with preference. A qualitative analysis of participant interviews reveals that this is due to shared evaluative criteria between complexity and quality. In other words, the things that make an image look complex are also what give the impression of time, effort and skill in a work of art.
You can download a copy of the thesis here: