Section: New Results

Social behaviors recognition

Participants : Wafa Benkaouar, Claudine Combe, Dominique Vaufreydaz [correspondant] .

Figure 5. On the left image, one can see the telemeter range in red, the foot detection (blue spot) and the angle view from the Kinect (in green). the middle and right image represent RGB camera en depth view from the Kinect.

Recognition of social behaviors is an unconscious innate cognitive process vital to human communication. This skill enables anticipation and increases interactive exchanges quality between humans. Among social behaviors, engagement is the expression of intention for interaction. During engagement phase, many non-verbal signals are used to communicate this intention to the partner, e.g. posture, gaze, spatial information, gestures, vocal cues. Within the context of frail or elderly people at home, companion robots must also be able to detect the engagement of humans in order to adapt their responses during interaction with humans to increase their acceptability.

Classical approaches in the domain are dealing with spatial information. Our hypothesis was that relative spatial information of people and robot are not discriminative in a home-like environment [15] . Our approach integrates multimodal features gathered using a robot companion equipped with a Kinect from Microsoft (see figure 5 ). Confronted to a robot centered dataset for multimodal social signal processing recorded in a home-like environment, the evaluation highlights its robustness and validates use of such technique in real environment (50% of error reduction). Our experimentations also confirm results from cognitive science domain [61] .