An Integrated Fusion Engine for Early Threat Detection Demonstrated in Public-Space Trials

Counter terrorism is a huge challenge for public spaces. Therefore, it is essential to support early detection of threats, such as weapons or explosives. An integrated fusion engine was developed for the management of a plurality of sensors to detect threats without disrupting the flow of commuters. The system improves security of soft targets ...

Rapid person re-identification retraining strategy for flexible deployment in new environments

Person re-identification (Re-ID) can be used to find the owner of lost luggage, to find suspects after a terrorist attack, or to fuse multiple sensors. Common state-of-the-art deep-learning technology performs well on a large public dataset but it does not generalize well to other environments, which makes it less suitable for practical...

Video-based fusion of multiple detectors to counter terrorism

Anonymized person re-identification in surveillance cameras

Person re-identification (Re-ID) is a valuable technique because it can assist in finding suspects after a terrorist attack. However, the machine learning algorithms for person Re-ID are usually trained on large datasets with images of many different people in a public space. This could pose privacy concerns for the people involved. One way to...

A triplet-learnt Coarse-to-Fine Reranking for Large Scale Vehicle Re-identification.

Vehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the...

Fast and accurate person re-identification with xception conv-net and C2F

Person re-identification (re-id) is the task of identifying a person of interest across disjoint camera views in a multi-camera system. This is a challenging problem due to the different poses, viewpoints and lighting conditions. Deeply learned systems have become prevalent in the person re-identification field as they are capable to deal with...

Fast and accurate person re-identification with Xception and Conv-Net and C2F

Automatische gedragsanalyse voor effectiever cameratoezicht in de openbare ruimte

To improve security in crowded environments, such as airports, shopping malls and railway stations, the number of surveillance cameras (CCTV) is rapidly increasing. However, the number of human operators remains limited and only a selection of the video streams can be observed. This makes it hard for an operator to be proactive. This paper gives...

Real-time tracking and fast retrieval of persons in multiple surveillance cameras of a shopping mall

The capability to track individuals in CCTV cameras is important for e.g. surveillance applications at large areas such as train stations, airports and shopping centers. However, it is laborious to track and trace people over multiple cameras. In this paper, we present a system for real-time tracking and fast interactive retrieval of persons in...

Re-identification of persons in multi-camera surveillance under varying viewpoints and illumination

The capability to track individuals in CCTV cameras is important for surveillance and forensics alike. However, it is laborious to do over multiple cameras. Therefore, an automated system is desirable. In literature several methods have been proposed, but their robustness against varying viewpoints and illumination is limited. Hence performance...