Joint Person Re-identification and Camera Network Topology Inference in Multiple Cameras
This addresses the problem of improving person re-identification accuracy in complex multi-camera systems for surveillance applications, but it is incremental as it builds on existing re-identification methods by adding topology inference.
The authors tackled the challenge of person re-identification in large-scale multi-camera networks by proposing a unified framework that jointly solves re-identification and camera network topology inference with minimal prior knowledge, and they introduced a new dataset (SLP) with nine non-overlapping cameras, showing promising experimental results.
Person re-identification is the task of recognizing or identifying a person across multiple views in multi-camera networks. Although there has been much progress in person re-identification, person re-identification in large-scale multi-camera networks still remains a challenging task because of the large spatio-temporal uncertainty and high complexity due to a large number of cameras and people. To handle these difficulties, additional information such as camera network topology should be provided, which is also difficult to automatically estimate, unfortunately. 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 effectively 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 consisting of nine non-overlapping cameras. Experimental results using our person re-identification and public datasets show that the proposed methods are promising for both person re-identification and camera topology inference tasks.