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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.
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.
| Original language | English |
|---|---|
| Title of host publication | Online proceedings of the TiGeR 2013 conference |
| Number of pages | 4 |
| Publication status | Published - 2013 |
Keywords
- gestures
- Information Gain
- object handover
- classification
- non-verbal communication
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