Interactive autonomous flock brush for non-photorealistic rendering. - Huang, Hsueh En. (2013)
Art and science are fundamental building blocks of human knowledge. Science is objective and structured. Art is subjective and expressive. In this thesis, we ask the question, "Could there be a logical side to Art?" Perhaps there exist fundamental elements or building blocks in Art that can be exploited and used in a parametric model? For the purposes of our research, we limit the discussion of Art to paintings and sketches. We examine art and art style discovery as a form of Non-photorealistic rendering (NPR). We designed a flock based brush model as the core mechanism for art style rendering. We used a stroke-based, evolutionary approach to NPR in the form of an Interactive Genetic Algorithm (IGA). By using our nature inspired brush model and IGA driven art style discovery prototype, we have re-created existing styles such as Impressionist, Sketch and Pointillism. Our system also serves as a platform to facilitate interactive art style discovery by way of an evolutionary process.