Relative information content of gestural features of non-verbal communication related to object-transfer interactions

Koene, Ansgar R. and Honisch, Juliane J. and Endo, Satoshi and Wing, Alan M. (2013) Relative information content of gestural features of non-verbal communication related to object-transfer interactions. In: EU FP7 CogLaboration project, 19-21 June 2013, Tilburg, the Netherlands.

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Abstract

In order to implement reliable, safe and smooth human-robot
object handover it will be necessary for service robots to
identify non-verbal communication gestures in real-time. This
study presents an analysis of the relative information content
in the gestural features that together constitute a
communication gesture. Based on this information theoretic
analysis we propose that the computational complexity of
gesture classification, for object handover, can be greatly
reduced by applying attention filters focused on static hand
shape and orientation.

Type of Work:

Conference or Workshop Item (Paper)

School/Faculty:

Colleges (2008 onwards) > College of Life & Environmental Sciences

Department:

Psychology

References:

Argyle, M. & Cook, M. (1976). Gaze and mutual gaze. Cambridge, UK: Cambridge University Press.
Bramer, M. (Eds.) (2007), Principles of Data Mining. London, UK: Springer.
Cakmak, M., Srinivasa, S.S., Lee, M.K., Kiesler, S., & Forlizzi, J. (2011). Using spatial and temporal contrast for
fluent robot-human handovers. Proc. 6th int. conf. on Human-robot interaction (pp. 489-496).
Grigore, E.C., Eder, K., Lenz, A., Skachek, S., Pipe, A.G.,
& Melhuish, C. (2011). Towards safe human-robot interaction. 12th Conference Towards Autonomous Robotic Systems (pp. 323–335). LNCS 6856, Springer.
Kirchner, N., Alempijevic, A., & Dissanayake, C. (2011). Nonverbal robot-group interaction using an imitated gaze cue. Proc. 6th int. conf. on Human-robot interaction (HRI ’11) (pp. 497-504). New York: ACM.
MacKay, D.J.C. (2007), Information Theory, Inference, and Learning Algorithms. Cambridge, UK: Cambridge University Press.
McNeill, I.D. (1992). Hand and mind: What gestures reveal about thought. Chicago: University of Chicago Press.
Morris D., Collett P., Marsh P. and O’SHaughnessy M. (1997). Gestures: their origins and distribution. New York: Stein & Day.
Nehaniv, C., Dautenhahn, K., Kubacki, J., Haegele, M., Parlitz, C., & Alami, R. (2005). A methodological approach relating the classification of gesture to identification of human intent in the context of humanrobot interaction,
Proc. IEEE Int. Workshop on Robot and Human Interactive Communication (pp. 371-377).
Ou, S., & Grupen, R. A. (2010). From manipulation to communicative gesture. Proc. of the 5th ACM/IEEE Int. Conf. on Human Robot Interaction (HRI 2010).
Riek, L.D., Rabinowitch, T.C., P., Bremner, A., Pipe, Fraser, M., & Robinson, P. (2010). Cooperative gestures: effective signaling for humanoid robots. Proc. of ACM Int. Conf. on Human-Robot Interaction.
Strabala, K., Lee, M.K., Dragan, A., Forlizzi, J., Srinivasa, S., Cakmak, M., & Micelli, V. (2013). Towards Seamless Human-Robot Handovers. Journal of Human-Robot
Interaction, 1(1), 1-23.

Date:

19 June 2013

Series/Collection Name:

TiGeR conference online proceedings

Keywords:

gestures; Information Gain; object handover; classification;.non-verbal communication

Subjects:

B Philosophy. Psychology. Religion > BF Psychology

Related URLs:

URL	URL Type
https://sites.google.com/site/arkoene/publications	Author

Remote Supplementary Files:

-	Excel table of gesture feature scores (direct download from site)
-	Videos of Participant gestures (access by request)

ID Code:

1802

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