Human detection and identification by robots using thermal and visual information in domestic environments

In this paper a robust system for enabling robots to detect and identify humans in domestic environments is proposed. Robust human detection is achieved through the use of thermal and visual information sources that are integrated to detect human-candidate objects, which are further processed in order to verify the presence of humans and their identity using face information in the thermal and visual spectrums. Face detection is used to verify the presence of humans, and face recognition to identify them. Active vision mechanisms are employed in order to improve the relative pose of a candidate object/person in case direct identification is not possible. The response of the different modules is characterized, and the proposed system is validated using image databases of real domestic environments, and human detection and identification benchmarks of the RoboCup@Home research community.