Combining dynamic head posegaze mapping with the robot conversational state for attention recognition in humanrobot interactions
Recognizing the visual focus of attention in the HRI context. Relying on head pose since eye gaze estimation is often impossible to achieve. Inspired from the behavioral models for body, head and gaze dynamics in gaze shifts. Exploiting the robot conversational state as context to reduce recognition ambiguities. Experiments on a public dataset where the robot Nao plays the role of an art guide.
head pose attention recognition hri context gaze non-verbal behavior