Human Machine Co-Creation. A Complementary Cognitive Approach to Creative Character Design Process Using GANs
This work addresses the challenge of enhancing creativity in character design for games and animation, though it appears incremental as it builds on existing GAN applications.
The research tackled the problem of augmenting character designers' abilities in visualizing and creating new characters for multimedia projects by developing a human-machine co-creation framework using GANs, with results showing that the generated concepts effectively served as cognitive substances to influence creative processes.
Recent advances in Generative Adversarial Networks GANs applications continue to attract the attention of researchers in different fields. In such a framework, two neural networks compete adversely to generate new visual contents indistinguishable from the original dataset. The objective of this research is to create a complementary codesign process between humans and machines to augment character designers abilities in visualizing and creating new characters for multimedia projects such as games and animation. Driven by design cognitive scaffolding, the proposed approach aims to inform the process of perceiving, knowing, and making. The machine generated concepts are used as a launching platform for character designers to conceptualize new characters. A labelled dataset of 22,000 characters was developed for this work and deployed using different GANs to evaluate the most suited for the context, followed by mixed methods evaluation for the machine output and human derivations. The discussed results substantiate the value of the proposed cocreation framework and elucidate how the generated concepts are used as cognitive substances that interact with designers competencies in a versatile manner to influence the creative processes of conceptualizing novel characters.