Person Re-Identification in Human Following Scenarios: An Experience with RGB-D Cameras

In order to acquire socially acceptable behaviors and seamlessly interact with humans, robots must employ robust solutions to identify, track and follow the interacting person in common environments. Robots nowadays typically are equipped with a camera which can be used to perform body as well as face recognition. However, as the person moves in the environment, the robot might lose track of the individual, e.g., behind corners or obstacles. We report our experience in the design and implementation of a solution that is able to track and follow a target person and that can re-identify the target if the line of sight is obstructed temporarily during following. Our initial experimentation highlights the impact of the employed sensor and the environment in which the person moves on the accuracy with which a persons can be re-identified in practice.