Abstract
The combination of a classifier system with an evolutionary image generation engine is explored. The framework is instantiated using an off-the-shelf face detection system and a general purpose, expression-based, genetic programming engine. By default, the classifier returns a binary output, which is inadequate to guide evolution. By retrieving information provided by intermediate results of the classification task, it became possible to develop a suitable fitness function. The experimental results show the ability of the system to evolve images that are classified as faces. A subjective analysis also reveals the unexpected nature and artistic potential of the evolved images.
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Machado, P., Correia, J., Romero, J. (2012). Expression-Based Evolution of Faces. In: Machado, P., Romero, J., Carballal, A. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2012. Lecture Notes in Computer Science, vol 7247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29142-5_17
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DOI: https://doi.org/10.1007/978-3-642-29142-5_17
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