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Designing Unconscious and Enactive Interaction for Interactive Movie Experience

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 12203)

Abstract

In a world full of sensors that gather personal data and digital solutions that use these data to provide feedback and personalized experiences, biofeedback is increasingly involved in the definition of new paradigms for tailoring interactions. Companies are collecting and using personal data to propose personalized services. Content providers are pushing users to produce data in order to create personalized storytelling experiences. In this context, the tech market is offering new low-cost solutions able to gather biodata. The paper reports the results of evidence-based explorations aimed at formalizing knowledge regarding the use of passive and unconscious interaction to control the fruition of storytelling artifacts. We investigate a new interaction paradigm that promise to seamlessly enable unconscious and enactive interactions for movie experiences. We propose the use of emotion recognition and eye-tracking as exploratory technologies that promise to be a potential contribution to richer access to the spectators’ emotional involvement. We reflect on disruptive power of non-invasive technologies, given by the possibility to be used for home-cinema experiences. Investigating on emotional states of users in their decision we leverage on the emotive-cognitive data as a matter of creation and enabling of tailored movie experiences. Our research intends to explore the possibility of extracting knowledge from recognition of facial expressions that will contribute to foster its use in real-time passive interaction using emotion recognition as a trigger of enactivity that is not limited to interactive storytelling but opens new scenarios in the design of proactive systems for screens, spaces and environments. Furthermore, we provide suggestions as guidelines for the design of enactive experiences that leverage on emotion recognition and eye-tracking.

Keywords

  • Real-time interaction
  • Enactive interaction
  • Eye-controlled interfaces
  • Emotion recognition
  • Evidence-based design research

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References

  1. Calvo, A., et al.: Eye tracking impact on quality-of-life of ALS patients. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2008. LNCS, vol. 5105, pp. 70–77. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70540-6_9

    CrossRef  Google Scholar 

  2. Tikka, P., Korkeakoulu, T.: Enactive cinema: simulatorium Eisensteinense. University of Art and Design Helsinki, Helsinki (2008)

    Google Scholar 

  3. Ekman, P., et al.: What the Face Reveals: Basic and Applied Studies of Spontaneous Expression Using the Facial Action Coding System (FACS). Oxford University Press, Oxford (1997)

    Google Scholar 

  4. Mitchell, W.J.: Me++: The Cyborg Self and the Networked City. MIT, Cambridge (2010)

    Google Scholar 

  5. Young, N.: The Virtual Self: How Our Digital Lives are Altering the World Around Us. McClelland & Stewart, Plattsburgh (2013)

    Google Scholar 

  6. Neff, G., Nafus, D.: Self-Tracking. The MIT Press, Cambridge (2016)

    CrossRef  Google Scholar 

  7. Lupton, D.: The digitally engaged patient: self-monitoring and self-care in the digital health era. Soc. Theory Health 11(3), 256–270 (2013). https://doi.org/10.1057/sth.2013.10

    CrossRef  Google Scholar 

  8. Quesenbery, W., Brooks, K.: Storytelling for User Experience: Crafting Stories for Better Design, p. 569 (2010)

    Google Scholar 

  9. Netflix. https://www.netflix.com/

  10. Slade, D.: Black Mirror: Bandersnatch. Netflix (2018)

    Google Scholar 

  11. McManus, S.: Minecraft: Story Mode. Telltale Games, Mojang (2015)

    Google Scholar 

  12. Buchta, R., Grylls, B.: You vs. Wild. Netflix (2019)

    Google Scholar 

  13. Burdine, R., Castucciano, J.: Puss in Book: Trapped in an Epic Tale. Netflix (2017)

    Google Scholar 

  14. Damasio, A.R.: Looking for Spinoza: Joy, Sorrow, and the Feeling Brain, First Harvest edn. Harcourt, Orlando, Toronto, London (2003)

    Google Scholar 

  15. Ekman, P.: Facial expressions of emotion: new findings, new questions. Psychol. Sci. 3(1), 34–38 (1992). https://doi.org/10.1111/j.1467-9280.1992.tb00253.x

    MathSciNet  CrossRef  Google Scholar 

  16. Tikka, P., Vuori, R., Kaipainen, M.: Narrative logic of enactive cinema: Obsession. Digit. Creat. 17(4), 205–212 (2006). https://doi.org/10.1080/14626260601074078

    CrossRef  Google Scholar 

  17. Maison, D., Pawłowska, B.: Using the FaceReader method to detect emotional reaction to controversial advertising referring to sexuality and homosexuality. In: Nermend, K., Łatuszyńska, M. (eds.) Neuroeconomic and Behavioral Aspects of Decision Making. SPBE, pp. 309–327. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62938-4_20

    CrossRef  Google Scholar 

  18. Kahneman, D.: Thinking, Fast and Slow, 1st pbk. edn. Farrar, Straus and Giroux, New York (2013)

    Google Scholar 

  19. Unity. Unity Technologies. https://unity.com/

  20. FaceReader. Noldus. https://doi.org/www.noldus.com/facereader

  21. Lewinski, P., den Uyl, T.M., Butler, C.: Automated facial coding: validation of basic emotions and FACS AUs in FaceReader. J. Neurosci. Psychol. Econ. 7(4), 227–236 (2014). https://doi.org/10.1037/npe0000028

    CrossRef  Google Scholar 

  22. Jansen, J.: Automated Identification and Measurement of Suppressed Emotions using Emotion Recognition Software, p. 16 (2015)

    Google Scholar 

  23. Mandolfo, M.: You trust me, and I feel it. Influence of foreign live biofeedback on interpersonal trust-related behaviour. Politecnico di Milano (2017)

    Google Scholar 

  24. Sumi, K., Ueda, T.: Micro-expression recognition for detecting human emotional changes. In: Kurosu, M. (ed.) HCI 2016. LNCS, vol. 9733, pp. 60–70. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39513-5_6

    CrossRef  Google Scholar 

  25. Schneier, B.: Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World, Norton Paperback. W.W. Norton & Company, New York, London (2016)

    Google Scholar 

  26. Polaine, A., Lovlie, L., Reason, B.: Service Design: From Insight to Implementation. Rosenfeld Media, Brooklyn (2013)

    Google Scholar 

  27. Pillan, M., Varisco, L., Bertolo, M.: Facing digital dystopias: a discussion about responsibility in the design of smart products. In: Alonso, M.B., Ozcan, E. (eds.) Proceedings of the Conference on Design and Semantics of Form and Movement - Sense and Sensitivity, DeSForM 2017, pp. 121–131. InTech (2017)

    Google Scholar 

  28. Varisco, L.: Personal Interaction Design: introducing the discussion on the consequences of the use of personal information in the design process. Ph.D. dissertation, Politecnico di Milano, Milan, Italy (2019)

    Google Scholar 

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Varisco, L., Interlandi, G. (2020). Designing Unconscious and Enactive Interaction for Interactive Movie Experience. In: Streitz, N., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. HCII 2020. Lecture Notes in Computer Science(), vol 12203. Springer, Cham. https://doi.org/10.1007/978-3-030-50344-4_26

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  • DOI: https://doi.org/10.1007/978-3-030-50344-4_26

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