Title: Evolutionary Image Composition Using Feature Covariance Matrices,
Abstract: Evolutionary algorithms have recently been used to create a wide range of
artistic work. In this paper, we propose a new approach for the composition of
new images from existing ones, that retain some salient features of the
original images. We introduce evolutionary algorithms that create new images
based on a fitness function that incorporates feature covariance matrices
associated with different parts of the images. This approach is very flexible
in that it can work with a wide range of features and enables targeting
specific regions in the images. For the creation of the new images, we propose
a population-based evolutionary algorithm with mutation and crossover operators
based on random walks. Our experimental results reveal a spectrum of
aesthetically pleasing images that can be obtained with the aid of our
evolutionary process.