Quality based frame selection for video face recognition

Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.

Effects of speeding and headway related variable message signs on driver behaviour and attitudes

This research project examined objective measures of driver behaviour and road users' perceptions on the usefulness and effectiveness of three specific VMS (Variable Message Signs) interventions to improve speeding and headway behaviours. The interventions addressed speeding behaviour alone (intervention 1), headway behaviour alone (intervention 2) and a combination of speeding and headway behaviour (intervention 3). Six VMS were installed along a segment of the Bruce Highway, with a series of three signs for each of the northbound and southbound traffic. Speeds and headway distances were measured with loop detectors installed before and after each VMS. Messages addressing speeding and headway were devised for display on the VMS. A driver could receive a message if they were detected as exceeding the posted speed limit (of 90km/hr) or if the distance to the vehicle in front was less than 2.0s. In addition to the on-road objective measurement of speeding and headway behaviours, the research project elicited self-reported responses to the speeding and headway messages from a sample of drivers via a community-based survey. The survey sought to examine the drivers' beliefs about the effectiveness of the signs and messages, and their views about the role, use, and effectiveness of VMS more generally.

Safety impacts of alcohol and other drugs in construction : development of an industry policy and cultural change management program

There is increasing concern about the impact of employees‟ alcohol and other drug (AOD) consumption on workplace safety and performance, particularly within the construction industry. While most Australian jurisdictions have identified this as a critical safety issue, information is limited regarding the prevalence of AODs in the workplace and there is limited evidential guidance regarding how to effectively and efficiently address such an issue. The current research aims to scientifically evaluate the use of AODs within the Australian construction industry in order to reduce the potential resulting safety and performance impacts and engender a cultural change in the workforce - to render it unacceptable to arrive at a construction workplace with impaired judgement from AODs. The study will adopt qualitative and quantitative methods to firstly evaluate the extent of general AOD use in the industry. Secondly, the development of an appropriate industry policy will adopt a non-punitive and rehabilitative approach developed in consultation with employers and employees across the infrastructure and building sectors, with the aim it be adopted nationally for adoption at the construction workplace. Finally, an industry specific cultural change management program and implementation plan will be developed through a nationally collaborative approach. Final results indicate that a proportion of those sampled in the construction sector may be at risk of hazardous alcohol consumption. A total of 286 respondents (58%) scored above the cut-off cumulative score for risky or hazardous alcohol. Other drug use was also identified as a major issue. Results support the need for evidence-based, preventative educational initiatives that are tailored to the industry. This paper will discuss the final survey and interview results.

Telephone support to rural and remote patients with heart failure : the Chronic Heart failure Assessment by Telephone (CHAT) study

Background Heart failure (HF) remains a condition with high morbidity and mortality. We tested a telephone support strategy to reduce major events in rural and remote Australians with HF, who have limited healthcare access. Telephone support comprised an interactive telecommunication software tool (TeleWatch) with follow-up by trained cardiac nurses. Methods Patients with a general practice (GP) diagnosis of HF were randomised to usual care (UC) or UC and telephone support intervention (UC+I) using a cluster design involving 143 GPs throughout Australia. Patients were followed for 12 months. The primary end-point was the Packer clinical composite score. Secondary end-points included hospitalisation for any cause, death or hospitalisation, as well as HF hospitalisation. Results Four hundred and five patients were randomised into CHAT. Patients were well matched at baseline for key demographic variables. The primary end-point of the Packer Score was not different between the two groups (P=0.98), although more patients improved with UC+I. There were fewer patients hospitalised for any cause (74 versus 114, adjusted HR 0.67 [95% CI 0.50-0.89], p=0.006) and who died or were hospitalised (89 versus 124, adjusted HR 0.70 [95% CI 0.53 – 0.92], p=0.011), in the UC+I vs UC group. HF hospitalisations were reduced with UC+I (23 versus 35, adjusted HR 0.81 [95% CI 0.44 – 1.38]), although this was not significant (p=0.43). There were 16 deaths in the UC group and 17 in the UC+I group (p=0.43). Conclusions Although no difference was observed in the primary end-point of CHAT (Packer composite score), UC+I significantly reduced the number of HF patients hospitalised amongst a rural and remote cohort. These data suggest that telephone support may be an efficacious approach to improve clinical outcomes in rural and remote HF patients.

Development and validation of the consumer disillusionment toward marketing activity scale

This study examines disillusioned consumers. The theory proposes that this is a group learning to lower their expectations of firm integrity and who, to avoid being let down, ignore marketing activity directly from the firm. This kind of exchange orientation develops as a response to consistent failure in perceptions of firm integrity. The research includes six studies, including over 600 adult consumers, to outline the development and validation of a measure of consumer disillusionment toward marketing activity. Completing the process provides a valid and reliable four-item measure. In addition, the study includes the assessment of the nomological validity of the construct. The nomological validation includes using cue utilization theory to predict that disillusioned consumers favor advertising that provides evidence of verifiable integrity. The validation experiment uses print advertising containing high and low verifiable integrity stimuli. Results confirm the theory with disillusioned consumers focusing less on the firm as source of information. Further, these consumers respond more favorably than non-disillusioned consumers to third party endorsers who serve to verify the firm's attempts to show integrity.

Access to cardiac rehabilitation does not equate to attendance

Background/Aims Timely access to appropriate cardiac care is critical for optimizing positive outcomes after a cardiac event. Attendance at cardiac rehabilitation (CR) remains less than optimal (10%–30%). Our aim was to derive an objective, comparable, geographic measure reflecting access to cardiac services after a cardiac event in Australia. Methods An expert panel defined a single patient care pathway and a hierarchy of the minimum health services for CR and secondary prevention. Using geographic information systems a numeric/alpha index was modelled to describe access before and after a cardiac event. The aftercare phase was modelled into five alphabetical categories: from category A (access to medical service, pharmacy, CR, pathology within 1 h) to category E (no services available within 1 h). Results Approximately 96% or 19 million people lived within 1 h of the four basic services to support CR and secondary prevention, including 96% of older Australians and 75% of the indigenous population. Conversely, 14% (64,000) indigenous people resided in population locations that had poor access to health services that support CR after a cardiac event. Conclusion Results demonstrated that the majority of Australians had excellent ‘geographic’ access to services to support CR and secondary prevention. Therefore, it appears that it is not the distance to services that affects attendance. Our ‘geographic’ lens has identified that more research on socioeconomic, sociological or psychological aspects to attendance is needed.

Assessing Cardiovascular Risk in Regional Areas: The Healthy Hearts – Beyond City Limits Program

Background: Cardiovascular disease (CVD) is more prevalent in regional and remote Australia compared to metropolitan areas. The aim of Healthy Hearts was to determine age and sex specific CVD risk factor levels and the potential value of national risk clinics. Methods: Healthy Hearts was an observational research study conducted in four purposefully selected higher risk communities in regional Victoria, Australia. The main outcome measures were the proportion of participants with CVD risk factors with group comparisons to determine the adjusted likelihood of elevated risk factor levels. Trained personnel used a standardized protocol over four weeks per community to measure CVD risk factor levels, estimate absolute CVD risk and provide feedback and advice. Results: A total of 2125 self-selected participants were assessed (mean age 58 ± 15 years, 57% women). Overall, CVD risk factors were highly prevalent. More men than women had ≥ 2 modifiable CVD risk factors (76% vs. 68%, p < .001), pre-existing CVD (20 vs. 15%, p < .01) and a major ECG abnormality requiring follow-up (15% vs. 7%, p < .001) . Less men reported depressive symptoms compared to women (28% vs. 22%, p < .01). A higher proportion of women were obese (adjusted OR 1.36, 95% CI 1.13 to 1.63), and physically inactive (adjusted OR 1.32, 95% CI 1.07 to 1.63). Conclusions: High CVD risk factor levels were confirmed for regional Victoria. Close engagement with individuals and communities provides scope for the application of regional risk management clinics to reduce the burden of CVD risk in regional Australia.

(Mis)Using Pulse Oximetry : A Review of Pulse Oximetry use in Acute Care Medical Wards

Background: Nurses routinely use pulse oximetry (SpO2) monitoring equipment in acute care. Interpretation of the reading involves physical assessment and awareness of parameters including temperature, haemoglobin, and peripheral perfusion. However, there is little information on whether these clinical signs are routinely measured or used in pulse oximetry interpretation by nurses. Aim: The aim of this study was to review current practice of SpO2 measurement and the associated documentation of the physiological data that is required for accurate interpretation of the readings. The study reviewed the documentation practices relevant to SpO2 in five medical wards of a tertiary level metropolitan hospital. Method: A prospective casenote audit was conducted on random days over a three-month period. The audit tool had been validated in a previous study. Results: One hundred and seventy seven episodes of oxygen saturation monitoring were reviewed. Our study revealed a lack of parameters to validate the SpO2 readings. Only 10% of the casenotes reviewed had sufficient physiological data to meaningfully interpret the SpO2 reading and only 38% had an arterial blood gas as a comparator. Nursing notes rarely documented clinical interpretation of the results. Conclusion: The audits suggest that medical and nursing staff are not interpreting the pulse oximetry results in context and that the majority of the results were normal with no clinical indication for performing this observation. This reduces the usefulness of such readings and questions the appropriateness of performing “routine” SpO2 in this context.

Shifting the Airline Business Model - Current Struggles of National Carriers to Become Profitable Passenger Experience Companies

National flag carriers are struggling for survival, not only due to classical reasons such as increase in fuel and tax or natural disasters, but largely due to the inability to quickly adapt to its competitive environment – the emergence of budget and Persian Gulf airlines. In this research, we investigate how airlines can transform their business models via technological and strategic capabilities to become profitable and sustainable passenger experience companies. To formulate recommendations, we analyze customer sentiments via social media to understand what people are saying about the airlines.

Importance of a resilient air services network to Australian remote, rural, and regional communities

Rural, regional, and remote settlements in Australia require resilient infrastructure to remain sustainable in a context characterized by frequent large-scale natural disasters, long distances between urban centers, and the pressures of economic change. A critical aspect of this infrastructure is the air services network, a system of airports, aircraft operators, and related industries that enables the high-speed movement of people, goods, and services to remote locations. A process of deregulation during the 1970s and 1980s resulted in many of these airports passing into local government and private ownership, and the rationalization of the industry saw the closure of a number of airlines and airports. This paper examines the impacts of deregulation on the resilience of air services and the contribution that they make to regional and rural communities. In particular, the robustness, redundancy, resourcefulness, and rapidity of the system are examined. The conclusion is that while the air services network has remained resilient in a situation of considerable change, the pressures of commercialization and the tendency to manage aspects of the system in isolation have contributed to a potential decrease in overall resilience.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.