Online Recognition-by- Tracking with Deep Appearance and Facial Features in a Robotic Environment

In the past few years, the number of robots being deployed in society has been continuously increasing. Robots are coming to family houses as personal assistants in domestic tasks and entertainers (e.g. toys) as well as in elderly care, handicap assistance, and nursing centers. The new generation of service robots have now to interact with humans in uncertain environments. For this, the robot needs to localize, engage and identify the target subject. The identification of the target could be done in different ways. Image-based face recognition is one example. It is a well-studied problem and state-of-the-art solutions achieve remarkable performance. However, most of the proposed solutions are not adapted to the robot environment. In this work, we explore a new approach to the problem of online person recognition. We present the Recognition-by-Tracking framework that uses pedestrian tracking in order to accumulate evidence about the face identities what leads to more accurate predictions.