Perceiving intimacy from both robot view and first-person view in dyadic human interaction

In this paper, we propose a framework to perceive the level of intimacy in dyadic human interactions from both robot perspective and first-person perspective. First of all, for catching the insight of human interaction with three different degrees of intimacy persons, namely normal, familiar and close, we have done a preliminary user study of social interaction. Next, from the field of social science and our study, we design four types of social interaction features, consisting of proxemics, non-verbal, verbal, and temporal features to categorize the intimacy level from observations, but including three of them reaches the best result. Finally, to validate our work here, several experiments have been conducted, and the results show that the framework perceives the aforementioned intimacy level with accuracy up to 86.11% in average.