Elements of information theory
Elements of information theory
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
SBIA '98 Proceedings of the 14th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Computer art: a personal recollection
Proceedings of the 5th conference on Creativity & cognition
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
On the origins of the term "Computational aesthetics"
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Defining computational aesthetics
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Identifying patterns from one-rule-firing cellular automata
Artificial Life
Increasing efficiency and quality in the automatic composition of three-move mate problems
ICEC'11 Proceedings of the 10th international conference on Entertainment Computing
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Informational dialogue with van Gogh's paintings
Computational Aesthetics'08 Proceedings of the Fourth Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Where is the beauty?: retrieving appealing VideoScenes by learning Flickr-based graded judgments
Proceedings of the 20th ACM international conference on Multimedia
Enhancing semantic features with compositional analysis for scene recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Semantic indexing and computational aesthetics: interactions, bridgesand boundaries
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Genetic Programming and Evolvable Machines
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In 1928, George D. Birkhoff introduced the Aesthetic Measure, defined as the ratio between order and complexity, and, in 1965, Max Bense analyzed Birkhoff's measure from an information theory point of view. In this paper, the concepts of order and complexity in an image (in our case, a painting) are analyzed in the light of Shannon entropy and Kolmogorov complexity. We also present a new vision of the creative process: the initial uncertainty, obtained from the Shannon entropy of the repertoire (palette), is transformed into algorithmic information content, defined by the Kolmogorov complexity of the image. From this perspective, the Birkhoff's Aesthetic Measure is presented as the ratio between the algorithmic reduction of uncertainty (order) and the initial uncertainty (complexity). The measures proposed are applied to several works of Mondrian, Pollock, and van Gogh.