Skip to main content

An Exploration of Visual Complexity

  • Conference paper
Diagrammatic Representation and Inference (Diagrams 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7352))

Included in the following conference series:

Abstract

Inspired by the contrast between ‘classical’ and ‘expressive’ visual aesthetic design, this paper explores the ‘visual complexity’ of images. We wished to investigate whether the visual complexity of an image could be quantified so that it matched participants’ view of complexity. An empirical study was conducted to collect data on the human view of the complexity of a set of images. The results were then related to a set of computational metrics applied to these images, so as to identify which objective metrics best encapsulate the human subjective opinion. We conclude that the subjective notion of ‘complexity’ is consistent both to an individual and to a group, but that it does not easily relate to the most obvious computational metrics.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Salimun, C., et al.: The effect of aesthetically pleasing composition on visual search performance. In: Nordic Human Computer Interaction Conference, pp. 422–431. ACM (2010)

    Google Scholar 

  2. Hartmann, J., Sutcliffe, A., De Angeli, A.: Investigating attractiveness in web user interfaces. In: Human Factors in Computing Systems (CHI) Conference, pp. 387–396 (2007)

    Google Scholar 

  3. Hassenzahl, M.: The Interplay of Beauty, Goodness, and Usability in Interactive Products. Human-Computer Interaction 19, 319–349 (2004)

    Article  Google Scholar 

  4. Kurosu, M., Kashimura, K.: Apparent usability vs inherent usability: experimental analysis on the determinants of the apparent usability. In: Human Factors in Computing Systems (CHI) Conference (1995)

    Google Scholar 

  5. Hartmann, J., Sutcliffe, A., De Angeli, A.: Towards a Theory of User Judgment of Aesthetics and User Interface Quality. ACM Transactions on Computer-Human Interaction 15(4), 15 (2008)

    Article  Google Scholar 

  6. Lavie, T., Tractinsky, N.: Assessing dimensions of perceived visual aesthetics of web sites. International Journal of Human-Computer Studies 60(3), 269–298 (2004)

    Article  Google Scholar 

  7. Knight, J., Pandir, M.: Homepage aesthetics: The search for preference factors and the challenges of subjectivity. Interacting with Computers 18, 1351–1370 (2006)

    Article  Google Scholar 

  8. Ngo, D., Teo, L., Byrne, J.G.: Modelling interface aesthetics. Information Sciences 152, 25–46 (2003)

    Article  Google Scholar 

  9. Ngo, D., Byrne, J.: Application of an aesthetic evaluation model to data entry screens. Computers in Human Behavior 17(2), 149–185 (2001)

    Article  Google Scholar 

  10. Michailidou, E., Harper, S., Bechhofer, S.: Visual Complexity and Aesthetic Perception of Web Pages. In: SIGDOC 2008 Conference, Lisbon, pp. 215–224 (2008)

    Google Scholar 

  11. Purchase, H.C., et al.: Investigating objective measures of web page aesthetics and usability. In: Lutteroth, C., Shen, H. (eds.) Australasian User Interface Conference, pp. 19–28. CPRIT, Perth (2011)

    Google Scholar 

  12. Donderi, D., McFadden, S.: Compressed file length predicts search time and errors on visual displays. Displays 26, 71–78 (2005)

    Article  Google Scholar 

  13. Donderi, D.: An information theory analysis of visual complexity and dissimilarity. Perception 35, 823–835 (2006)

    Article  Google Scholar 

  14. Forsythe, A., et al.: Predicting beauty: Fractal dimension and visual complexity in art. British Journal of Psychology 102, 49–70 (2001)

    Article  Google Scholar 

  15. Oliva, A., et al.: Identifying the Perceptual Dimensions of Visual Complexity of Scenes. In: Cognitive Science Conference (2004)

    Google Scholar 

  16. Snodgrass, J.G., Vanderwart, M.: A Standardized Set of 260 Pictures. Norms for Name Agreement, Image Agreement, Familiarity and Visual Complexity. Journal of Experimental Psychology: Human Learning and Memory 6(2), 174–215 (1980)

    Article  Google Scholar 

  17. Mario, I., et al.: Image complexity measure: a human criterion free approach. In: North American Fuzzy Information Processing Society, pp. 241–246 (2005)

    Google Scholar 

  18. Salimun, C., Purchase, H.C., Simmons, D.: Visual aesthetics in computer interface design: does it matter? In: 34th European Conference on Visual Perception, p. 220 (2011)

    Google Scholar 

  19. International Commission on Illumination: Colour Difference, http://en.wikipedia.org/wiki/Color_difference#CIE76 (accessed February 28, 2012)

  20. Robertson, A.: The CIE 1976 color-difference formulae. Colour Research and Application 2(1), 7–11 (1997)

    Google Scholar 

  21. Sharma, G.: Digital Color Imaging. IEEE Transactions on Image Processing 6(7), 901–932 (1997)

    Article  Google Scholar 

  22. Willow Garage: OpenCV, http://opencv.willowgarage.com/ (accessed February 28, 2012)

  23. Ding, L., Goshtasby, A.: On the Canny edge detector. Pattern Recognition 34, 721–725 (2001)

    Article  MATH  Google Scholar 

  24. Canny, J.: A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)

    Article  Google Scholar 

  25. ImageMagick Studio LLC: ImageMagick, http://www.imagemagick.org/ (accessed February 28, 2012)

  26. Brace, N., Kemp, R., Snelgar, R.: SPSS for Psychologists, 2nd edn. Palgrave Macmillan (2003)

    Google Scholar 

  27. Ware, C.: Information Visualisation: Perception for Design. Elsevier (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Purchase, H.C., Freeman, E., Hamer, J. (2012). An Exploration of Visual Complexity. In: Cox, P., Plimmer, B., Rodgers, P. (eds) Diagrammatic Representation and Inference. Diagrams 2012. Lecture Notes in Computer Science(), vol 7352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31223-6_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31223-6_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31222-9

  • Online ISBN: 978-3-642-31223-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics