A Complexity Approach for Identifying Aesthetic Composite Landscapes
Inhaltsverzeichnis
Referenz
Adrian Carballal, Rebeca Perez, Antonino Santos, Luz Castro: A Complexity Approach for Identifying Aesthetic Composite Landscapes. In: EvoMUSART 2014, S. 50-61.
DOI
http://link.springer.com/10.1007/978-3-662-44335-4_5
Abstract
The present paper describes a series of features related to complexity which may allow to estimate the complexity of an image as a whole, of all the elements integrating it and of those which are its focus of attention. Using a neural network to create a classifier based on those features an accuracy over 85% in an aesthetic composition binary classification task is achieved. The obtained network seems to be useful for the purpose of assessing the Aesthetic Composition of landscapes. It could be used as part of a media device for facilitating the creation of images or videos with a more professional aesthetic composition.
Extended Abstract
Bibtex
@incollection{
year={2014},
isbn={978-3-662-44334-7},
booktitle={Evolutionary and Biologically Inspired Music, Sound, Art and Design},
volume={8601},
series={Lecture Notes in Computer Science},
editor={Romero, Juan and McDermott, James and Correia, João},
doi={10.1007/978-3-662-44335-4_5},
title={A Complexity Approach for Identifying Aesthetic Composite Landscapes},
url={http://dx.doi.org/10.1007/978-3-662-44335-4_5 http://de.evo-art.org/index.php?title=A_Complexity_Approach_for_Identifying_Aesthetic_Composite_Landscapes },
publisher={Springer Berlin Heidelberg},
author={Carballal, Adrian and Perez, Rebeca and Santos, Antonino and Castro, Luz},
pages={50-61},
language={English}
}
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