Coherent nature of crowd movement allows representing the crowd motion using sparse features. However, surveillance videos recorded at different periods of time are likely to have different crowd densities and motion characteristics. These varying scene properties necessitate use of different models for an effective representation of behaviour at different periods. In this study, a density awar...

This paper deals with real-time image processing of crowded outdoor scenes with the objective of creating an effective traffic management system that monitors urban settings (urban intersections, streets after athletic events, etc.). The proposed system can detect, track, and monitor both pedestrians (crowds) and vehicles. We describe the characteristics of the tracker that is based on a new de...

This paper presents a solution to the problem of tracking people within crowded scenes. The aim is to maintain individual object identity through a crowded scene which contains complex interactions and heavy occlusions of people. Our approach uses the strengths of two separate methods; a global object detector and a localised frame by frame tracker. A temporal relationship model of torso detect...

ELECT The increasing number of cameras and a handful of human operators to monitor the video inputs from hundreds of cameras leave the system ill equipped to fulfil the task of detecting anomalies. Thus, there is a dire need to automatically detect the regions that require immediate attention for more effective and proactive surveillance. A framework that utilises the temporal variations in the...