Generating Abstract Comics

We investigate a new approach to comic generation that explores the process of generating the contents of a panel given the contents of all previous panels. Our approach is based on leading discourse theories for comics by McCloud (panel transitions) and Cohn (narrative grammar), unified by cognitive theories of inference in visual language. We apply these theories to comics whose panel parameters are abstract geometric shapes and their positions, contributing a computational realization of McCloud’s and Cohn’s comics theories, as well as a modular algorithm that affords further experimentation and evaluation of visual discourse theories.

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