Designing and evaluating a social gaze-control system for a humanoid robot

Abolfazl Zaraki, Daniele Mazzei, Manuel Giuliani, Danilo De Rossi

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)

Abstract

This paper describes a context-dependent social gaze-control system implemented as part of a humanoid social robot. The system enables the robot to direct its gaze at multiple humans who are interacting with each other and with the robot. The attention mechanism of the gaze-control system is based on features that have been proven to guide human attention: nonverbal and verbal cues, proxemics, the visual field of view, and the habituation effect. Our gaze-control system uses Kinect skeleton tracking together with speech recognition and SHORE-based facial expression recognition to implement the same features. As part of a pilot evaluation, we collected the gaze behavior of 11 participants in an eye-tracking study. We showed participants videos of two-person interactions and tracked their gaze behavior. A comparison of the human gaze behavior with the behavior of our gaze-control system running on the same videos shows that it replicated human gaze behavior 89% of the time.

Original languageEnglish
Article number6736067
Pages (from-to)157-168
Number of pages12
JournalIEEE Transactions on Human-Machine Systems
Volume44
Issue number2
DOIs
Publication statusPublished - Apr 2014

Keywords

  • Active vision
  • context-dependent social gaze behavior
  • human-robot interaction
  • scene analysis
  • social attention

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