Soft biometrics for social adaptive robots

Soft biometric analysis aims at recognizing personal traits that provide some information about an individual. In this paper, we present a real-time system able to automatically recognize soft biometric traits to enhance the capability of a social robot, Pepper, in this case, to understand characteristics of people present in the environment and to properly interact with them. In particular, the proposed system is able to estimate several traits simultaneously, such as gender, age, the presence of eyeglasses and beard, of people in the field of view of the robot. Our hypothesis is that adding these capabilities to a social robot improves and makes more believable its social behavior. Results of the preliminary evaluation seems to support this hypothesis