Title :
Collaborative multi-camera face recognition and tracking
Author :
Jason Rambach;Marco F. Huber;Mark R. Balthasar;Abdelhak M. Zoubir
Author_Institution :
DFKI GmbH, Kaiserslautern, Germany
Abstract :
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.
Keywords :
"Cameras","Face","Face recognition","Target tracking","Image recognition","Target recognition"
Conference_Titel :
Advanced Video and Signal Based Surveillance (AVSS), 2015 12th IEEE International Conference on
DOI :
10.1109/AVSS.2015.7301765