Ecological Gestures for HRI: the GEE Corpus
Maxence Girard-Rivier, Romain Magnani, V{\'e}ronique Auberg{\'e}, Yuko Sasa, Liliya Tsvetanova, Fr{\'e}d{\'e}ric Aman, Clarisse Bayol
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As part of a human-robot interaction project, we are interested by gestural modality as one of many ways to communicate. In order to develop a relevant gesture recognition system associated to a smart home butler robot. Our methodology is based on an IQ game-like Wizard of Oz experiment to collect spontaneous and implicitly produced gestures in an ecological context. During the experiment, the subject has to use non-verbal cues (i.e. gestures) to interact with a robot that is the referee. The subject is unaware that his gestures will be the focus of our study. In the second part of the experiment, we asked the subjects to do the gestures he had produced in the experiment, those are the explicit gestures. The implicit gestures are compared with explicitly produced ones to determine a relevant ontology. This preliminary qualitative analysis will be the base to build a big data corpus in order to optimize acceptance of the gesture dictionary in coherence with the ``socio-affective glue'' dynamics.