Collaborative Multi-Camera Face Recognition and Tracking

Jason Raphael Rambach, Marco F. Huber, Mark R. Balthasar, Abdelhak M. Zoubir

In: IEEE. International Conference on Advanced Video and Signal based Surveillance (AVSS-2015) August 25-28 Karlsruhe Germany IEEE 2015.


In this paper, a framework for collaborative face recognition from video sequences in a multi-camera environment is proposed. Collaboration between cameras allows for higher recognition performance in both the common and non-common field-of-view (FOV) cases. For the latter, the appearance of an object in a nearby camera is predicted using the last tracked position of the object paired with a time-of-arrival model between camera pairs. An experiment using four cameras in an office environment confirms the applicability and performance gains of the proposed framework .

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence