Generating Abstract Comics

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10045)

Abstract

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.

Keywords

Intelligent narrative technologies Comics Narrative generation 

References

  1. 1.
    Cohn, N.: The Visual Language of Comics: Introduction to the Structure and Cognition of Sequential Images. Bloomsbury, London (2013)Google Scholar
  2. 2.
    Cohn, N.: Narrative conjunction’s junction function: the interface of narrative grammar and semantics in sequential images. J. Pragmatics 88, 105–132 (2015)CrossRefGoogle Scholar
  3. 3.
    Cohn, N. (ed.): The Visual Narrative Reader. Bloomsbury Publishing, New York (2016)Google Scholar
  4. 4.
    Gerrig, R.J., Bernardo, A.B.I.: Readers as problem-solvers in the experience of suspense. Poetics 22(6), 459–472 (1994)CrossRefGoogle Scholar
  5. 5.
    Grice, H.P.: Logic and conversation. In: Cole, P., Morgan, J.L. (eds.) Syntax and Semantics 3: Speech Arts. Elsevier, New York (1975)Google Scholar
  6. 6.
    Heider, F., Simmel, M.: An experimental study of apparent behavior. Am. J. Psychol. 57(2), 243–259 (1944)CrossRefGoogle Scholar
  7. 7.
    Jhala, A., Young, R.M.: Cinematic visual discourse: representation, generation, and evaluation. IEEE Trans. Comput. Intell. AI Games 2(2), 69–81 (2010)CrossRefGoogle Scholar
  8. 8.
    Jhala, A., Young, R.M.: A discourse planning approach to cinematic camera control for narratives in virtual environments. In: AAAI, vol. 5, pp. 307–312 (2005)Google Scholar
  9. 9.
    Magliano, J.P., Kopp, K., Higgs, K., Rapp, D.N.:. Filling in the gaps: memory implications for inferring missing content in graphic narratives. Discourse Processes (2016)Google Scholar
  10. 10.
    Mani, I.: Computational modeling of narrative. Synth. Lect. Hum. Lang. Technol. 5(3), 1–142 (2012)CrossRefGoogle Scholar
  11. 11.
    McCloud, S.: Understanding Comics: The Invisible Art. Harper Collins, New York (1993)Google Scholar
  12. 12.
    Montfort, N., Fedorova, N.: Small-scale systems and computational creativity. In: Proceedings of the 3rd International Conference on Computational Creativity, pp. 82–86 (2012)Google Scholar
  13. 13.
    Myers, J.L., Shinjo, M., Duffy, S.A.: Degree of causal relatedness and memory. J. Mem. Lang. 26(4), 453–465 (1987)CrossRefGoogle Scholar
  14. 14.
    Pérez y Pérez, R., Morales, N., Rodríguez, L.: Illustrating a computer generated narrative. In: Proceedings of the 3rd International Conference on Computational Creativity, pp. 103–110 (2012)Google Scholar
  15. 15.
    Pérez y Pérez, R., Sharples, M.: MEXICA: a computer model of a cognitive account of creative writing. J. Exp. Theor. Artif. Intell. 13(2), 119–139 (2001)CrossRefMATHGoogle Scholar
  16. 16.
    Pirolli, P.: Information Foraging Theory: Adaptive Interaction with Information. Oxford University Press, New York (2007)CrossRefGoogle Scholar
  17. 17.
    Saraceni, M.: Relatedness: aspects of textual connectivity in comics. In: Cohn, N. (ed.) The Visual Narrative Reader, Chap. 5, pp. 115–128. Bloomsbury (2016)Google Scholar
  18. 18.
    Smith, G., Whitehead, J.: Analyzing the expressive range of a level generator. In: Proceedings of the 2010 Workshop on Procedural Content Generation in Games at the 5th Interational Conference on the Foundations of Digital Games (2010)Google Scholar
  19. 19.
    Zwaan, R.A., Radvansky, G.A.: Situation models in language comprehension and memory. Psychol. Bull. 123(2), 162–185 (1998)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceNorth Carolina State UniversityRaleighUSA

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