Disease surveillance and epidemiological investigations in Australian fur seals

This study is the first systematic investigation into the disease status of Australian fur seals and one of very few conducted on Southern Hemisphere pinnipeds. It contributes to the understanding of Australian fur seal disease ecology and so informs the conservation management of this species

Mutual obligation? Regulating by supervision and surveillance in Australian income support policy

Through an analysis of speeches by government ministers, documents and regulations, this article examines the Australian national government’s surveillance of unemployed people through what is known as Activity Testing, and more specifically as Mutual Obligation. It seeks to merge the social policy analysis of Mutual Obligation with a surveillance perspective in order to delve deeper into the underlying nature of the policy and its implications for people who are unemployed. It does this by 1. Outlining the neo-liberal political theory underlying these policies; 2. Illustrating the nature and extent of surveillance of people in receipt of income support, and 3. Employing Foucault’s concepts of the technologies of domination and the self to highlight the controlling and coercive aspects of Mutual Obligation in achieving certain of the Government’s political and policy objectives. In doing so, the analysis will make visible something of the power exerted over the disadvantaged while subject to such surveillance.

ID scanning, the media and the politics of urban surveillance in an Australian regional city

Computerised ID scanning technologies have permeated many urban night-time economies in Australia, the United States, Canada and the United Kingdom. This paper documents how one media organisation’s overt and tacit approval of ID scanners helped to normalise this form of surveillance as a precondition of entry into most licensed venues in the Australian city of Geelong. After outlining how processes of governance “from above” and “from below” interweave to generate distinct political and media demands for strategies to prevent localised crime problems, a chronological reconstruction of media reports over a three-and-a half year period demonstrates how ID scanning became the centrepiece of a holistic reform strategy to combat alcohol-related violence in this nightclub precinct. Several discursive techniques helped to normalise this “technological fix”, while suppressing critical discussion of viable concerns over information privacy, data security and system networking. These
included pairing reports of an initial “signal crime” with examples of “virtual victimhood” to stress the urgency of a radical surveillance-based response, which was supported by anecdotal statements from key “primary definers” highlighting the success of this initiative in targeting a wider population of antisocial “others”. The implications of these reporting practices are discussed in light of the media’s central role in reforming the Geelong night-time economy and broader trends in using novel surveillance technologies to combat urban crime problems at the expense of alternative measures that protect individual liberty.

Multiple camera coordination in a surveillance system

We present a distributed surveillance system that uses multiple cheap static cameras to track multiple people in indoor environments. The system has a set of Camera Processing Modules and a Central Module to coordinate the tracking tasks among the cameras. Since each object in the scene can be tracked by a number of cameras, the problem is how to choose the most appropriate camera for each object. This is important given the need to deal with limited resources (CPU, power etc.). We propose a novel algorithm to allocate objects to cameras using the object-to-camera distance while taking into account occlusion. The algorithm attempts to assign objects in the overlapping field of views to the nearest camera, which can see the object without occlusion. Experimental results show that the system can coordinate cameras to track people and can deal well with occlusion.

Tracking and surveillance in wide-area spatial environments using the abstract hidden markov model.

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of the well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.

An immunological approach to raising alarms in video surveillance

Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three detectors for detecting abnormal activity are generated using negative selection. Tracks gathered by people’s movements in a room are used for experimentation and results have shown that the classifier is able to discriminate abnormal from normal activities in terms of both trajectory and time spent at a location.

Comparative evaluation of pedestrian detection methods for mobile bus surveillance

We present a comparative evaluation of the state-of-art algorithms for detecting pedestrians in low frame rate and low resolution footage acquired by mobile sensors. Four approaches are compared: a) The Histogram of Oriented Gradient (HoG) approach [1]; b) A new histogram feature that is formed by the weighted sum of both the gradient magnitude and the filter responses from a set of elongated Gaussian filters [2] corresponding to the quantised orientation, called Histogram of Oriented Gradient Banks (HoGB) approach; c) The codebook based HoG feature with branch-and-bound (efficient subwindow search) algorithm [3] and; d) The codebook based HoGB approach. Results show that the HoG based detector achieves the highest performance in terms of the true positive detection, the HoGB approach has the lowest false positives whilst maintaining a comparable true positive rate to the HoG, and the codebook approaches allow computationally efficient detection.

Pedestrian detection for mobile bus surveillance

In this paper, we present a system for pedestrian detection involving scenes captured by mobile bus surveillance cameras in busy city streets. Our approach integrates scene localization, foreground and background separation, and pedestrian detection modules into a unified detection framework. The scene localization module performs a two stage clustering of the video data. In the first stage, SIFT Homography is applied to cluster frames in terms of their structural similarities and second stage further clusters these aligned frames in terms of lighting. This produces clusters of images which are differential in viewpoint and lighting. A kernel density estimation (KDE) method for colour and gradient foreground-background separation are then used to construct background model for each image cluster which is subsequently used to detect all foreground pixels. Finally, using a hierarchical template matching approach, pedestrians can be identified. We have tested our system on a set of real bus video datasets and the experimental results verify that our system works well in practice.

Context aware privacy in visual surveillance

In this paper we present preliminary work implementing dynamic privacy in public surveillance. The aim is to maximise the privacy of those under surveillance, while giving an observer access to sufficient information to perform their duties. As these aspects are in conflict, a dynamic approach to privacy is required to balance the system's purpose with the system's privacy. Dynamic privacy is achieved by accounting for the situation, or context, within the environment. The context is determined by a number of visual features that are combined and then used to determine an appropriate level of privacy.

Distributed query processing for mobile surveillance

Addressing core issues in mobile surveillance, we present an architecture for querying and retrieving distributed, semi-permanent multi-modal data through challenged networks with limited connectivity. The system provides a rich set of queries for spatio-temporal querying in a surveillance context, and uses the network availability to provide best quality of service. It incrementally and adaptively refines the query, using data already retrieved that exists on static platforms and on-demand data that it requests from mobile platforms. We demonstrate the system using a real surveillance system on a mobile 20 bus transport network coupled with static bus depot infrastructure. In addition, we show the robustness of the system in handling different conditions in the underlying infrastructure by running simulations on a real, but historic dataset collected in an offline manner.