Abstract
Gaze direction is an important communicative cue. In order to use this cue for human-robot interaction, software needs to be developed that enables the estimation of head pose. We began by designing an application that is able to make a good estimate of the head pose, and, contrary
to earlier head pose estimation approaches, that works for non-optimal lighting conditions. Initial results show that our approach using multiple networks trained with differing datasets, gives a good estimate of head pose, and it works well in poor lighting conditions and with low-resolution images. We validated our head pose estimation method using a custom built database of images of human heads. The actual head poses were measured using a trakStar (Ascension Technologies) six-degrees-of-freedom sensor. The head pose estimation algorithm allows us to assess a person’s focus of attention, which allows robots to react in a timely fashion to dynamic human communicative cues.
Original language | English |
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Title of host publication | Proceedings of the 6th International Conference on Human-Robot Interaction (HRI 2011), March 6-9, 2011 |
Editors | A. Billard, P. Kahn, J.A, Adams, G. Trafton |
Place of Publication | New York |
Publisher | Association for Computing Machinery, Inc |
Pages | 277-278 |
ISBN (Print) | 978-1-4503-0561-7 |
DOIs | |
Publication status | Published - 2011 |
Event | 6th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2011 - Lausanne, Switzerland Duration: 6 Mar 2011 → 9 Mar 2011 Conference number: 6 |
Conference
Conference | 6th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2011 |
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Abbreviated title | HRI 2016 |
Country/Territory | Switzerland |
City | Lausanne |
Period | 6/03/11 → 9/03/11 |