Zaraki, Abolfazl ORCID: https://orcid.org/0000-0001-6204-7865, Banitalebi Dehkordi, Maryam ORCID: https://orcid.org/0000-0002-3205-6637, Mazzei, Daniele and De Rossi, Danilo 2014. An experimental eye-tracking study for the design of a context-dependent social robot blinking model. Presented at: Living Machines 2014, Milan, Italy, 30 July - 1 August 2014. Published in: Duff, Armin, Lepora, Nathan F., Mura, Anna, Prescott, Tony J. and Verschure, Paul F. M. J. eds. Biomimetic and Biohybrid Systems: Third International Conference, Living Machines 2014, Milan, Italy, July 30 – August 1, 2014. Proceedings. Lecture Notes in Computer Science , vol.8608 Springer Verlag, pp. 356-366. 10.1007/978-3-319-09435-9_31 |
Abstract
Human gaze and blinking behaviours have been recently considered, to empower humanlike robots to convey a realistic behaviour in a social human-robot interaction. This paper reports the findings of our investigation on human eye-blinking behaviour in relation to human gaze behaviour, in a human-human interaction. These findings then can be used to design a humanlike eye-blinking model for a social humanlike robot. In an experimental eye-tracking study, we showed to 11 participants, a 7-minute video of social interactions of two people, and collected their eye-blinking and gaze behaviours with an eye-tracker. Analysing the collected data, we measured information such as participants’ blinking rate, maximum and minimum blinking duration, number of frequent (multiple) blinking, as well as the participants’ gaze directions on environment. The results revealed that participants’ blinking rate in a social interaction are qualitatively correlated to the gaze behaviour, as higher number of gaze shift increased the blinking rate. Based on the findings of this study, we can propose a context-dependent blinking model as an important component of the robot’s gaze control system that can empower our robot to mimic human blinking behaviour in a multiparty social interaction.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Status: | Published |
Schools: | Engineering |
Publisher: | Springer Verlag |
Last Modified: | 11 Mar 2023 02:16 |
URI: | https://orca.cardiff.ac.uk/id/eprint/128999 |
Citation Data
Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |