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A Probabilistic Model of Motor Resonance for Embodied Gesture Perception

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5773))

Abstract

Basic communication and coordination mechanisms of human social interaction are assumed to be mediated by perception-action links. These links ground the observation and understanding of others in one’s own action generation system, as evidenced by immediate motor resonances to perceived behavior. We present a model to endow virtual embodied agents with similar properties of embodied perception. With a focus of hand-arm gesture, the model comprises hierarchical levels of motor representation (commands, programs, schemas) that are employed and start to resonate probabilistically to visual stimuli of a demonstrated movement. The model is described and evaluation results are provided.

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References

  1. Amit, R., Mataric, M.: Learning movement sequences from demonstration. In: ICDL 2002: Proceedings of the 2nd International Conference on Development and Learning, pp. 203–208 (2002)

    Google Scholar 

  2. Brass, M., Bekkering, H., Prinz, W.: Movement observation affects movement execution in a simple response task. Acta Psychologica 106(1–2), 3–22 (2001)

    Article  Google Scholar 

  3. Buccino, G., Binkofski, F., Fink, G.R., Fadiga, L., Fogassi, L., Gallese, V., Seitz, R.J., Zilles, K., Rizzolatti, G., Freund, H.-J.: Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study. European Journal of Neuroscience 13, 400–404 (2001)

    Google Scholar 

  4. Buchsbaum, D., Blumberg, B.: Imitation as a first step to social learning in synthetic characters: a graph-based approach. In: SCA 2005: Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation, New York, pp. 9–18 (2005)

    Google Scholar 

  5. Calinon, S., Billard, A.: Incremental learning of gestures by imitation in a humanoid robot. In: HRI 2007: Proceedings of the ACM/IEEE international conference on Human-robot interaction, pp. 255–262. ACM, New York (2007)

    Google Scholar 

  6. Calinon, S., Billard, A.: Learning of Gestures by Imitation in a Humanoid Robot, pp. 153–177. Cambridge University Press, Cambridge (2007)

    Book  Google Scholar 

  7. Demiris, J., Hayes, G.R.: Imitation as a dual-route process featuring predictive and learning components: a biologically plausible computational model. In: Imitation in animals and artifacts, pp. 327–361. MIT Press, Cambridge (2002)

    Google Scholar 

  8. Dijksterhuis, A., Bargh, J.: The perception-behavior expressway: Automatic effects of social perception on social behavior. Advances in Experimental Social Psychology, vol. 33, pp. 1–40 (2001)

    Google Scholar 

  9. Flash, T., Hochner, B.: Motor primitives in vertebrates and invertebrates. Journal of Current Opinion in Neurobiololgy 15, 660–666 (2005)

    Article  Google Scholar 

  10. Gutemberg, G.-F., Yiannis, A.: A language for human action. Computer 40(5), 42–51 (2007)

    Article  Google Scholar 

  11. Hamilton, A., Grafton, S.: The motor hierarchy: From kinematics to goals and intentions. In: Attention and Performance 22. Oxford University Press, Oxford (2007)

    Google Scholar 

  12. Kopp, S., Graeser, O.: Imitation learning and response facilitation in embodied agents. In: Gratch, J., Young, M., Aylett, R.S., Ballin, D., Olivier, P. (eds.) IVA 2006. LNCS (LNAI), vol. 4133, pp. 28–41. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. Kopp, S., Wachsmuth, I.: Synthesizing multimodal utterances for conversational agents. Journal of Computer Animation and Virtual Worlds 15(1), 39–52 (2004)

    Article  Google Scholar 

  14. Kopp, S., Wachsmuth, I., Bonaiuto, J., Arbib, M.: Imitation in embodied communication – from monkey mirror neurons to artificial humans. In: Wachsmuth, I., Lenzen, M., Knoblich, G. (eds.) Embodied Communication in Humans and Machines, pp. 357–390. Oxford University Press, Oxford (2008)

    Chapter  Google Scholar 

  15. Fadiga, G.P.L., Fogassi, L., Rizzolatti, G.: Motor facilitation during action observation: a magnetic stimulation study. Journal of Neurophysiology 73(6), 2608–2611 (1995)

    Google Scholar 

  16. Oztop, E., Chaminade, T., Franklin, D.: Human-humanoid interaction: is a humanoid robot perceived as a human? In: 2004 4th IEEE/RAS International Conference on Humanoid Robots, vol. 2, pp. 830–841 (2004)

    Google Scholar 

  17. Robert, C.P.: Prior feedback: A Bayesian approach to maximum likelihood estimation. Technical Report 91-49C (1991)

    Google Scholar 

  18. Schilbach, L., Wohlschlaeger, A.M., Kraemer, N.C., Newen, A., Shah, N.J., Fink, G.R., Vogeley, K.: Being with virtual others: Neural correlates of social interaction. Neuropsychologia 44(5), 718–730 (2006)

    Article  Google Scholar 

  19. Schutz-Bosbach, S., Prinz, W.: Perceptual resonance: action-induced modulation of perception. Journal of Trends in Cognitive Sciences 11(8), 349–355 (2007)

    Article  Google Scholar 

  20. Shon, A., Storz, J., Rao, R.: Towards a real-time bayesian imitation system for a humanoid robot. In: 2007 IEEE International Conference on Robotics and Automation, pp. 2847–2852 (2007)

    Google Scholar 

  21. Verma, R., Rao, D.: Goal-based imitation as probabilistic inference over graphical models. Advances in neural information processing systems (18), 1393–1400 (2006)

    Google Scholar 

  22. Wilson, M., Knoblich, G.: The case for motor involvement in perceiving conspecifics. Psychological Bulletin 131(3), 460–473 (2005)

    Article  Google Scholar 

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Sadeghipour, A., Kopp, S. (2009). A Probabilistic Model of Motor Resonance for Embodied Gesture Perception. In: Ruttkay, Z., Kipp, M., Nijholt, A., Vilhjálmsson, H.H. (eds) Intelligent Virtual Agents. IVA 2009. Lecture Notes in Computer Science(), vol 5773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04380-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-04380-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04379-6

  • Online ISBN: 978-3-642-04380-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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