| Autor: |
Samy Lakhal, Alexandre Darmon, Jean-Philippe Bouchaud, Michael Benzaquen |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Physical Review Research, Vol 2, Iss 2, p 022058 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2643-1564 |
| DOI: |
10.1103/PhysRevResearch.2.022058 |
| Popis: |
We revisit the long-standing question of the relation between image appreciation and its statistical properties. We generate two different sets of random images well distributed along three measures of entropic complexity. We run a large-scale survey in which people are asked to sort the images by preference, which reveals maximum appreciation at intermediate entropic complexity. We show that the algorithmic complexity of the coarse-grained images, expected to capture structural complexity while abstracting from high frequency noise, is a good predictor of preferences. Our analysis suggests that there might exist some universal quantitative criteria for aesthetic judgment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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