Designing and Evaluating a Social Gaze-Control System for a Humanoid Robot

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 o...

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Bibliographic Details
Published in:IEEE transactions on human-machine systems 2014-04, Vol.44 (2), p.157-168
Main Authors: Zaraki, Abolfazl, Mazzei, Daniele, Giuliani, Manuel, De Rossi, Danilo
Format: Article
Language:English
Subjects:
Active vision
Applied sciences
Artificial intelligence
Biological and medical sciences
Computer science
control theory
systems
context-dependent social gaze behavior
Control systems
Control theory. Systems
Exact sciences and technology
Face
Face recognition
Feature extraction
Fundamental and applied biological sciences. Psychology
Human
human-robot interaction
Humanoid
Humanoid robots
Pattern recognition. Digital image processing. Computational geometry
Pilots
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Robot kinematics
Robotics
Robots
Running
scene analysis
social attention
Social interactions. Communication. Group processes
Social psychology
Speech and sound recognition and synthesis. Linguistics
Speech recognition
Tracking
Visualization
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Summary: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.
ISSN:2168-2291
2168-2305
DOI:10.1109/THMS.2014.2303083