Christopher S. Madden

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Tracking single individuals as they move across disjoint camera views is a challenging task since their appearance may vary significantly between views. Major changes in appearance are due to different and varying illumination conditions and the deformable geometry of people. These effects are hard to estimate and take into account in real-life(More)
Several techniques have been proposed to date to build colour invariants between camera views with varying illumination conditions. In this paper, we propose to improve colour invariance by using data-dependent techniques. To this aim, we compare the effectiveness of his-togram stretching, illumination filtration, full histogram equalisation and controlled(More)
Automatic placement of surveillance cameras in arbitrary buildings is a challenging task, and also one that is essential for efficient deployment of large scale surveillance networks. Existing approaches for automatic camera placement are either limited to a small number of cameras, or constrained in terms of the building layouts to which they can be(More)
This paper investigates a method of visualising internet traffic data using the underlying spherical nature of the globe. The method uses data about the traffic between Autonomous Systems (ASes) that are the communications on the public internet system. This data is displayed as a set of nodes with connecting edges overlaying the three-dimensional spherical(More)
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An accurate estimate of camera overlap is a key enabler for efficient network-wide surveillance processing (e.g. inter-camera tracking), especially in large-scale surveillance networks. Techniques based on contradictions in pair-wise occupancy data, such as the exclusion approach, have advantages in robustness and efficiency that make them particularly well(More)