Feature selection and novelty in computational aesthetics

Authors:
João Correia;Penousal Machado;Juan Romero;Adrian Carballal
Affiliations:
CISUC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal;CISUC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal;Faculty of Computer Science, University of A Coruña, Coruña, Spain;Faculty of Computer Science, University of A Coruña, Coruña, Spain
Venue:
EvoMUSART'13 Proceedings of the Second international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Year:
2013

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Abstract

An approach for exploring novelty in expression-based evolutionary art systems is presented. The framework is composed of a feature extractor, a classifier, an evolutionary engine and a supervisor. The evolutionary engine exploits shortcomings of the classifier, generating misclassified instances. These instances update the training set and the classifier is re-trained. This iterative process forces the evolutionary algorithm to explore new paths leading to the creation of novel imagery. The experiments presented and analyzed herein explore different feature selection methods and indicate the validity of the approach.