Generating Personalized Abstract Art Paintings by using People's Life Energy Distribution

Authors : Furkan Ayas, Feriştah Dalkiliç

Pages : 6-14

View : 51 | Download : 75

Publication Date : 2023-08-20

Article Type : Research Article

Abstract :Data visualization, which is essentially the visual expression of data through mathematical calculations, is a highly effective method for transferring and understanding data. The right data visualization, selected or developed with data and people in mind, has an important role in improving the quality of conveying the relationships, meanings, information, structures and hidden properties of data to individuals from different fields of expertise and enables them to work together. Data visualization has been a subject that has evolved and progressed in different ways throughout history and has finally reached today\'s computer technology and conditions. The improved facilities of today\'s computer such as high computing power has brought data visualization methods to a new horizon. Also the changing definition of the data has expanded the boundaries of the data visualization. Today, data is obtained from many different sources such as; IoT, Embedded systems, Social data, Business data and Real-Life data. Our study is also inspired by the Real-Life. We developed a visualization system based on real-life botanical trees and using humans as data. Throughout history, computer science and other branches of science have used art as a subject in various studies. In our study, we bring science and art together again to develop a way of expressing people through art. Thus, we developed an artistic visualization system that uses the activities of people\'s lives as data and generates artistic visuals inspired by abstract art paintings. Through this work, we have created an art style with a visualization system that manages to produce artistic visuals while adhering to its mathematical foundations.
Keywords : Data Visualization, Creative Algorithms, Computational Creativity, Neural Style Transferring, Abstract Art