with the increase of the number of cameras installed across a video surveillance network, the ability of security staffs to attentively scan all the video feeds actually decreases. therefore, the need for an intelligent system that operates as a tracking system is vital for security personnel to do their jobs well. tracking people as they move through a camera network with non-overlapping field...

Person re-identification concerns the matching of pedestrians across disjoint camera views. Due to the changes of viewpoints, lighting conditions and camera features, images of the same person from different views always appear differently, and thus feature representations across disjoint camera views of the same person follow different distributions. In this work, we propose an effective, low ...

This paper systematically investigates the effectiveness of different visual feature coding schemes for facilitating the learning of time-delayed dependencies among disjoint multi-camera views. Accurate inter-camera dependency estimation across nonoverlapping camera views is non-trivial especially in crowded scenes where inter-object occlusion can be severe and frequent, and when the degree of ...

Activity modelling and unusual event detection in a network of cameras is challenging particularly when the camera views are not overlapped. We show that it is possible to detect unusual events in multiple disjoint cameras as context-incoherent patterns, through incremental learning of time delayed dependencies between distributed local activities observed within and across camera views. Specif...

Existing methods for person re-identification (Re-ID) are mostly based on supervised learning which requires numerous manually labeled samples across all camera views training. Such a paradigm suffers the scalability issue since in real-world Re-ID application, it is difficult to exhaustively label abundant identities over multiple disjoint views. To this end, we propose progressive deep method...

A surveillance session can be defined as the period between an individual’s entrance into a surveillance system, and their exit. Utilising this framework enables personal features, such as clothing and height estimates, to become invariant for the duration of the surveillance session. These can then be used as session-based biometrics for matching an individual uniquely as they move throughout ...