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.
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Carballal, A., Perez, R., Santos, A., Castro, L. (2014). A Complexity Approach for Identifying Aesthetic Composite Landscapes. In: Romero, J., McDermott, J., Correia, J. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2014. Lecture Notes in Computer Science, vol 8601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44335-4_5
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DOI: https://doi.org/10.1007/978-3-662-44335-4_5
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