A Context Space Model for Detecting Anomalous Behaviour in Video Surveillance

Having a good automatic anomalous human behaviour detection is one of the goals of smart surveillance systems’ domain of research. The automatic detection addresses several human factor issues underlying the existing surveillance systems. To create such a detection system, contextual information needs to be considered. This is because context is required in order to correctly understand human behaviour. Unfortunately, the use of contextual information is still limited in the automatic anomalous human behaviour detection approaches. This paper proposes a context space model which has two benefits: (a) It provides guidelines for the system designers to select information which can be used to describe context; (b)It enables a system to distinguish between different contexts. A comparative analysis is conducted between a context-based system which employs the proposed context space model and a system which is implemented based on one of the existing approaches. The comparison is applied on a scenario constructed using video clips from CAVIAR dataset. The results show that the context-based system outperforms the other system. This is because the context space model allows the system to considering knowledge learned from the relevant context only.

Surveillance and slander : Eleanor Dark in the 1940s and 1950s

Examines the effects of national surveillance and local right-wing intimidation on the literary works of author Eleanor Dark during the 1940s and 1950s in Australia. Reason Dark was subjected to national surveillance and right-wing intimidation; Relationship of Dark with local and national security forces; Accusations against the Dark family; Censorship faced by writers.

Improved Subject Identification in Surveillance Video using Super Resolution

The time consuming and labour intensive task of identifying individuals in surveillance video is often challenged by poor resolution and the sheer volume of stored video. Faces or identifying marks such as tattoos are often too coarse for direct matching by machine or human vision. Object tracking and super-resolution can then be combined to facilitate the automated detection and enhancement of areas of interest. The object tracking process enables the automatic detection of people of interest, greatly reducing the amount of data for super-resolution. Smaller regions such as faces can also be tracked. A number of instances of such regions can then be utilized to obtain a super-resolved version for matching. Performance improvement from super-resolution is demonstrated using a face verification task. It is shown that there is a consistent improvement of approximately 7% in verification accuracy, using both Eigenface and Elastic Bunch Graph Matching approaches for automatic face verification, starting from faces with an eye to eye distance of 14 pixels. Visual improvement in image fidelity from super-resolved images over low-resolution and interpolated images is demonstrated on a small database. Current research and future directions in this area are also summarized.

A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

A database for person re-identification in multi-camera surveillance networks

Person re-identification involves recognising individuals in different locations across a network of cameras and is a challenging task due to a large number of varying factors such as pose (both subject and camera) and ambient lighting conditions. Existing databases do not adequately capture these variations, making evaluations of proposed techniques difficult. In this paper, we present a new challenging multi-camera surveillance database designed for the task of person re-identification. This database consists of 150 unscripted sequences of subjects travelling in a building environment though up to eight camera views, appearing from various angles and in varying illumination conditions. A flexible XML-based evaluation protocol is provided to allow a highly configurable evaluation setup, enabling a variety of scenarios relating to pose and lighting conditions to be evaluated. A baseline person re-identification system consisting of colour, height and texture models is demonstrated on this database.

Surveillance of dengue fever virus: a review of epidemiological models and early warning systems

Dengue fever is one of the world’s most important vector-borne diseases. The transmission area of this disease continues to expand due to many factors including urban sprawl, increased travel and global warming. Current preventative techniques are primarily based on controlling mosquito vectors as other prophylactic measures, such as a tetravalent vaccine are unlikely to be available in the foreseeable future. However, the continually increasing dengue incidence suggests that this strategy alone is not sufficient. Epidemiological models attempt to predict future outbreaks using information on the risk factors of the disease. Through a systematic literature review, this paper aims at analyzing the different modeling methods and their outputs in terms of accurately predicting disease outbreaks. We found that many previous studies have not sufficiently accounted for the spatio-temporal features of the disease in the modeling process. Yet with advances in technology, the ability to incorporate such information as well as the socio-environmental aspect allowed for its use as an early warning system, albeit limited geographically to a local scale.

Welfare reform, surveillance and new paternalism

This paper discusses the situation of welfare claimants, often constructed as faulty citizens and flawed welfare subjects. Many are on the receiving end of complex, multi-layered forms of surveillance aimed at securing socially responsible and compliant behaviours. In Australia, as in other Western countries, neoliberal economic regimes with their harsh and often repressive treatment of welfare recipients operate in tandem with a burgeoning and costly arsenal of CCTV and other surveillance and governance assemblages. The Australian Government’s Centrelink BasicsCard is but one example of welfare surveillance, whereby a percentage of a welfare claimant’s allowances must be spent on ‘approved’ items. The BasicsCard which has perhaps slipped under the radar of public discussion and is expanding nationally, raises significant questions about whether it is possible to encourage people to take responsibility for themselves if they no longer have real control over the most important aspects of their lives. Resistance and critical feedback, particularly from Indigenous people, points to a loss of dignity around the imposition of income management, operational complexity and denial of individual agency in using the BasicsCard, alongside the contradiction of apparently becoming ‘self-reliant’ through being income managed by the welfare state. This paper highlights the lack of solid evidence for the implementation/imposition of the BasicsCard and points to the importance of developing critically based research to inform the enactment of evidence based policy, also acting as a touchstone for governmental accountability. In highlighting issues around the BasicsCard this paper makes a contribution to the largely under discussed area of income management and the growth of welfare surveillance in Australia.

Post-discharge surveillance : can patients reliably diagnose surgical wound infections?

Post-discharge surgical wound infection surveillance is an important part of many infection control programs. It is frequently undertaken by patient self-assessment, prompted either by a telephone or postal questionnaire. To assess the reliability of this method, 290 patients were followed for six weeks postoperatively. Their wounds were photographed and also covertly assessed for signs of infection by two experienced infection control nurses (ICNs). Patients also responded to a postal questionnaire seeking evidence of infection at both week four and week six post-surgery. Correlation between the patient's assessment of their wound and the ICNs diagnosis was poor (r=0.37) with a low positive predictive value (28.7%), although negative predictive value was high (98.2%). Assessment of photos for signs of infection by two experienced clinicians also correlated poorly with the ICNs diagnosis of infection (r=0.54). The patient's recall of prescription of an antibiotic by their general practitioner (GP) for wound infection during the postoperative period correlated best with the ICNs diagnosis (r=0.76). This latter measure, particularly when confirmed by the GP in those patients reporting an infection, appears to provide the most valid and resource efficient marker of post-discharge surgical wound infection.

Upper-body morbidity after breast cancer : incidence and evidence for evaluation, prevention, and management within a prospective surveillance model of care

The purpose of this paper is to review the incidence of upper-body morbidity (arm and breast symptoms, impairments, and lymphedema), methods for diagnosis, and prevention and treatment strategies. It was also the purpose to highlight the evidence base for integration of prospective surveillance for upper-body morbidity within standard clinical care of women with breast cancer. Between 10% and 64% of women report upper-body symptoms between 6 months and 3 years after breast cancer, and approximately 20% develop lymphedema. Symptoms remain common into longer-term survivorship, and although lymphedema may be transient for some, those who present with mild lymphedema are at increased risk of developing moderate to severe lymphedema. The etiology of morbidity seems to be multifactorial, with the most consistent risk factors being those associated with extent of treatment. However, known risk factors cannot reliably distinguish between those who will and will not develop upper-body morbidity. Upper-body morbidity may be treatable with physical therapy. There is also evidence in support of integrating regular surveillance for upper-body morbidity into the routine care provided to women with breast cancer, with early diagnosis potentially contributing to more effective management and prevention of progression of these conditions.

Implementation Guide for Surveillance of Staphylococcus aureus Bacteraemia -- [Consultation Edition]

The Implementation Guide for the Hospital Surveillance of SAB has been produced by the Healthcare Associated Infection (HAI) Technical Working Group of the Australian Commission on Safety and Quality in Health Care (ACSQHC), and endorsed by the HAI Advisory Group. The Technical Working Group is made up of representatives invited from surveillance units and the ACSQHC, who have had input into the preparation of this Guide. The Guide has been developed to ensure consistency in reporting of SAB across public and private hospitals to enable accurate national reporting and benchmarking. It is intended to be used by Australian hospitals and organisations to support the implementation of healthcare associated Staphylococcus aureus bacteraemia(SAB) surveillance using the endorsed case definition1 in the box below and further detail in the Data Set Specification.

Implementation Guide for Surveillance of Clostridium Difficile Infection -- [Consultation Edition]

The Implementation Guide for hospital surveillance of Clostridium difficile infection (CDI) has been produced by the Healthcare Associated Infection (HAI) Technical Working Group of the Australian Commission on Safety and Quality in Health Care (ACSQHC), and endorsed by the HAI Advisory Group. State jurisdictions and the ACSQHC have representatives on the Technical Working Group, and have had input into this document. (See acknowledgements on inside front cover)...

Implementation Guide for Surveillance of Central Line Associated Bloodstream Infection -- [Consultation Edition]

The implementation guide for the surveillance of CLABSI in intensive care units (ICU) was produced by the Healthcare Associated Infection (HAI) Technical Working Group of the Australian Commission on Safety and Quality in Health Care(ACSQHC), and endorsed by the ACSQHC HAI Advisory Committee. State surveillance units, the ACSQHC and the Australian and New Zealand Intensive Care Society (ANZICS) have representatives on the Technical Working Group, and have provided input into this document.