Evolving art using measures for symmetry, compositional balance and liveliness
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Transcript of Evolving art using measures for symmetry, compositional balance and liveliness
Evolving art using measures for symmetry, compositional
balance and liveliness
Eelco den HeijerVrije Universiteit Amsterdam
Outline• Introduction
• Symmetry
• Compositional balance
• Liveliness
• Experiments & Results
• Conclusions
• Future work
Introduction
• Unsupervised evolutionary art
• No human in the loop
• Aesthetic Measures
• fitness functions, computational aesthetics
• impact on `style’ of resulting image
• Global Contrast Factor, Ralph/ Ross Bell curve, Machado/ Cardoso, Benford Law
Symmetry & Balance• Symmetry
• Ubiquitous - it’s everywhere...
• Important in design, architecture
• ‘Hard-wired’ in human visual system?
• It’s role in visual art is not straightforward
• Compositional Balance
• Important in graphic design & visual art
• Processing fluency (Reber)
Motivation• Evo* paper 2011
• Multi-Objective Evolutionary art
• Multiple aesthetic measures
• Some combinations work well, some combinations do not (same `dimension’, opposing directions)
• Need for aesthetic measures that work on other ‘dimensions’ (e.g. symmetry)
Research Questions
When using unsupervised evolution (i.e. without a human in the loop);
1.Is it possible to evolve symmetric images?
2.Is it possible to evolve `balanced’ images?
3.Do the aesthetic measures for symmetry and balance mix well with other aesthetic measures?
Related work (1)• Several aesthetic measures in unsupervised
evolutionary art
• Machado & Cardoso (1998)
• Image complexity & Processing complexity
• Matkovic et al (2005)
• Global Constrast Factor
• Ross & Ralph (2006)
• Bell curve
• Several others
Related work (2)
• Ngo et al (2000)
• Symmetry in GUI screens
• Bauerly and Liu (2005, 2008)
• Aethetic evaluation of symmetry in web pages
Calculating Symmetry• Select two areas (depending on orientation)
• Mirror the second area (using the proper axis)
• Calculate difference in intensity values between all pixels in the two areas
• If difference is below 0.05 diff=1, else diff=0
Symmetry? Relax...• Is too much symmetry a good thing?
• Finding a `sweet spot’ for symmetry
• We did not find a value for this `sweet spot’ in literature
• we used 0.8 in our experiments
Compositional balance• Compute visual similarity (or distance) between
image regions
• Stricker & Orengo image distance function (1995)
• Image is `compressed’ to a feature vector
Stricker & Orengo
Calculating Balance
• Select two areas (depending on symmetry type)
• Determine feature vector for both areas
• Calculate Stricker & Orengo difference
Liveliness• Using only symmetry would lead to a lot of
monochrome images (since they are perfectly symmetrical...)
• Same goes for compositional balance; two halves of a monochrome image have identical feature vectors
• So, we need additional constraints
• Not only symmetrical, but ‘lively’ too
Liveliness: how?• A simple and naive measure for ‘interestingness’
• Our definition;interestingness = ‘having a high distribution of intensity values’
• Calculate entropy of intensity values (x=intensity value):
Experiments
• Unsupervised
• No humans...
• Genetic programming
• `Pixel paradigm’
Experiment Setup
1 Symmetry (bilateral) (+ liveliness)
2 Relaxed symmetry (+ liveliness)
3 Compositional balance (+ liveliness)
4 Multi-objective (NSGA-II); a) Symmetry (all directions)b) livelinessc) Global Contrast Factor
1. Bilateral symmetry
2. Bilateral symmetry (relaxed)
3. Compositional Balance
4.Combination (GCF + L + Sym)
Conclusions (1)• Our evolutionary art system has no
difficulty in evolving symmetric images
• Relatively `easy’ aesthetic measure (rapid fitness progression)
Conclusions (2)• It is possible to control the `amount’ of
symmetry in an unsupervised evolutionary art system
• Compositional balance
• Images often ‘just‘ symmetrical
• Might need additional ‘penalty’
Future work• Other distance functions for compositional
balance (e.g. based on texture)
• Experiments with symmetry using different representations (e.g. SVG)
• Good test for compositional balance measure
• Improve compositional balance measure
• Detect blobs, determine their weight, etc.
Thank you!Images and papers at
http://www.few.vu.nl/~eelco Questions?