Joint person re-identification and camera network topology inference in multiple cameras

Abstract In this study, we propose a unified framework which jointly solves both person re-identification and camera network topology inference problems with minimal prior knowledge about the environments. The proposed framework takes general multi-camera network environments into account and can be applied to online person re-identification in large-scale multi-camera networks. In addition, to show the superiority of the proposed framework, we provide a new person re-identification dataset with full annotations, named SLP , captured in the multi-camera network. Experimental results using our re-identification and public datasets show that the proposed methods are promising for both person re-identification and camera topology inference tasks.