A genetically generated drone A/V composition using video analysis as a 'disturbance factor' to the fitness function

Abstract

This paper discusses the development of an audio-visual composition based on genetic algorithms strategies. The genetic algorithm's fitness function dynamically adjusts the optimisation targets linked to the mechanisms responsible for the generating of drone soundscapes. The fitness function continuously changes based on the results of an analysis of the visual elements of the artwork thus acting as disturbance factor. In doing so, the audio material never achieves full optimisation and constantly shapes itself. The paper offers both a technical and aesthetic analysis of the development of the composition.