Local inter-session variability modelling for object classification

Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

Examining fan attitudes toward sponsor brands using social identity frameworks

The majority of academic research has attempted to explain the effectiveness of sponsorship activities by focusing on individual outcomes (Cornwell, Weeks, & Roy, 2005). The current research builds upon the limited empirical studies that examine sponsorship outcomes using group behaviour theories (Cornwell & Coote, 2005; Gwinner & Swanson, 2003; Madrigal, 2000, 2001). Specifically, this study closely examines tenets of social identity theory (Brewer, 1991; Tajfel & Turner, 1979) within the context of sports sponsorship to test effects of team identification on attitudes toward associated sponsor brands. 1,840 unique surveys were collected from fans of the Queensland Maroons and New South Wales Blues rugby clubs over four timepoints during the 2012 State of Origin series. The results suggest that social identity effects were present regarding ingroup bias toward sponsor brands. Local sponsors were rated higher than non-local sponsors, suggesting that local brands may benefit more from sponsorship.

Assessing the discipline : an analysis of Australian journalism review articles 2000-2010

In recent years, there has been much discussion about the quality of research published by Australian journalism academics, without much empirical evidence about what kind of work the field actually engages in. This paper attempts to map the relatively young field of Australian journalism research by presenting the results of a comprehensive meta-analysis of articles published in the Australian Journalism Review between 2000 and 2010. Our findings show that, contrary to evidence elsewhere, a gender balance exists in terms of absolute numbers of authors, although a "glass-ceiling effect" is still discernible. Queensland universities dominate the publications, and most studies employ qualitative rather than quantitative methods. Journalism education is the most popular topic, yet a large variety of topics are evident overall. Despite a heavy focus on Australia, and to a smaller extent New Zealand, the journal also displays a sizeable international touch.

Impact of passenger group dynamics on an airport evacuation process using an agent-based model

The safety of passengers is a major concern to airports. In the event of crises, having an effective and efficient evacuation process in place can significantly aid in enhancing passenger safety. Hence, it is necessary for airport operators to have an in-depth understanding of the evacuation process of their airport terminal. Although evacuation models have been used in studying pedestrian behaviour for decades, little research has been done in considering the evacuees’ group dynamics and the complexity of the environment. In this paper, an agent-based model is presented to simulate passenger evacuation process. Different exits were allocated to passengers based on their location and security level. The simulation results show that the evacuation time can be influenced by passenger group dynamics. This model also provides a convenient way to design airport evacuation strategy and examine its efficiency. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Resection-intersection bundle adjustment revisited

Bundle adjustment is one of the essential components of the computer vision toolbox. This paper revisits the resection-intersection approach, which has previously been shown to have inferior convergence properties. Modifications are proposed that greatly improve the performance of this method, resulting in a fast and accurate approach. Firstly, a linear triangulation step is added to the intersection stage, yielding higher accuracy and improved convergence rate. Secondly, the effect of parameter updates is tracked in order to reduce wasteful computation; only variables coupled to significantly changing variables are updated. This leads to significant improvements in computation time, at the cost of a small, controllable increase in error. Loop closures are handled effectively without the need for additional network modelling. The proposed approach is shown experimentally to yield comparable accuracy to a full sparse bundle adjustment (20% error increase) while computation time scales much better with the number of variables. Experiments on a progressive reconstruction system show the proposed method to be more efficient by a factor of 65 to 177, and 4.5 times more accurate (increasing over time) than a localised sparse bundle adjustment approach.

Airports of the future : improving operation, security and experience

The final report for the ARC project "Airports of the Future". It contains the findings and recommendations provided by the various teams to the industry partners.

Agent-based modelling simulation case study : assessment of airport check-in and evacuation process by considering group travel behaviour of air passengers

Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Agent-based application on different boarding strategies

In this paper we implemented six different boarding strategies (Wilma, Steffen, Reverse Pyramid, Random, Blocks and By letter) in order to minimize boarding time and turnaround time for Boeing 777 and Airbus 380 aircrafts by using Agent-based modelling approach. In the simulation, we divided passengers into six different categories which are group size more than 5 people, passengers with child, gold members, first class passengers, business class passengers and economy class passengers. Results from the simulation demonstrates Reverse Pyramid method is the best boarding method for Boeing 777 and Steffen method is the best boarding method for Airbus 380.

Factors that influence young people's mental health help‐seeking behaviour : a study based on the Health Belief Model

Aim To identify key predictors and moderators of mental health ‘help-seeking behavior’ in adolescents. Background Mental illness is highly prevalent in adolescents and young adults; however, individuals in this demographic group are among the least likely to seek help for such illnesses. Very little quantitative research has examined predictors of help-seeking behaviour in this demographic group. Design A cross-sectional design was used. Methods A group of 180 volunteers between the ages of 17–25 completed a survey designed to measure hypothesized predictors and moderators of help-seeking behaviour. Predictors included a range of health beliefs, personality traits and attitudes. Data were collected in August 2010 and were analysed using two standard and three hierarchical multiple regression analyses. Findings The standard multiple regression analyses revealed that extraversion, perceived benefits of seeking help, perceived barriers to seeking help and social support were direct predictors of help-seeking behaviour. Tests of moderated relationships (using hierarchical multiple regression analyses) indicated that perceived benefits were more important than barriers in predicting help-seeking behaviour. In addition, perceived susceptibility did not predict help-seeking behaviour unless individuals were health conscious to begin with or they believed that they would benefit from help. Conclusion A range of personality traits, attitudes and health beliefs can predict help-seeking behaviour for mental health problems in adolescents. The variable ‘Perceived Benefits’ is of particular importance as it is: (1) a strong and robust predictor of help-seeking behaviour, and; (2) a factor that can theoretically be modified based on health promotion programmes.

Locating people in video from semantic descriptions : a new database and approach

The location of previously unseen and unregistered individuals in complex camera networks from semantic descriptions is a time consuming and often inaccurate process carried out by human operators, or security staff on the ground. To promote the development and evaluation of automated semantic description based localisation systems, we present a new, publicly available, unconstrained 110 sequence database, collected from 6 stationary cameras. Each sequence contains detailed semantic information for a single search subject who appears in the clip (gender, age, height, build, hair and skin colour, clothing type, texture and colour), and between 21 and 290 frames for each clip are annotated with the target subject location (over 11,000 frames are annotated in total). A novel approach for localising a person given a semantic query is also proposed and demonstrated on this database. The proposed approach incorporates clothing colour and type (for clothing worn below the waist), as well as height and build to detect people. A method to assess the quality of candidate regions, as well as a symmetry driven approach to aid in modelling clothing on the lower half of the body, is proposed within this approach. An evaluation on the proposed dataset shows that a relative improvement in localisation accuracy of up to 21 is achieved over the baseline technique.

Agent-based modelling of aircraft boarding methods

We implemented six different boarding strategies (Wilma, Steffen, Reverse Pyramid, Random, Blocks and By letter) in order to investigate boarding times for Boeing 777 and Airbus 380 aircraft. We also introduce three new boarding methods to find the optimum boarding strategy. Our models explicitly simulate the behaviour of groups of people travelling together and we explicitly simulate the timing to store their luggage as part of the boarding process. Results from the simulation demonstrates the Reverse Pyramid method is the best boarding method for Boeing 777, and the Steffen method is the best boarding method for Airbus 380. For the new suggested boarding methods, aisle first boarding method is the best boarding strategy for Boeing 777 and row arrangement method is the best boarding strategy for Airbus 380. Overall best boarding strategy is aisle first boarding method for Boeing 777 and Steffen method for Airbus 380.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

Estrogen deficiency-associated bone loss in the maxilla: A methodology to quantify the changes in the maxillary intra-radicular alveolar bone in an ovariectomized rat osteoporosis model

The effects of estrogen deficiency on bone characteristics are site-dependent, with the most commonly studied sites being appendicular long bones (proximal femur and tibia) and axial bones (vertebra). The effect on the maxillary and mandibular bones is still inconsistent and requires further investigation. This study was designed to evaluate bone quality in the posterior maxilla of ovariectomized rats in order to validate this site as an appropriate model to study the effect of osteoporotic changes. Methods: Forty-eight 3-month-old female Sprague-Dawley rats were randomly divided into two groups: an ovariectomized group (OVX, n=24) and Sham-operated group (SHAM, n=24). Six rats were randomly sacrificed from both groups at time points 8, 12, 16 and 20 weeks. The samples from tibia and maxilla were collected for Micro CT and histological analysis. For the maxilla, the volume of interest (VOI) area focused on the furcation areas of the first and second molar. Trabecular bone volume fraction (BV/TV, %), trabecular thickness (Tb.Th.), trabecular number (Tb.N.), trabecular separation (Tb.Sp.), and connectivity density (Conn.Dens) were analysed after Micro CT scanning. Results: At 8 weeks the indices BV/TV, Tb.Sp, Tb.N and Conn.Dens showed significant differences (P<0.05) between the OVX and SHAM groups in the tibia. Compared with the tibia, the maxilla developed osteoporosis at a later stage, with significant changes in maxillary bone density only occurring after 12 weeks. Compared with the SHAM group, both the first and second molars of the OVX group showed significantly decreased BV/TV values from 12 weeks, and these changes were sustained through 16 and 20 weeks. For Tb.Sp, there were significant increases in bone values for the OVX group compared with the SHAM group at 12, 16 and 20 weeks. Histological changes were highly consistent with Micro CT results. Conclusion: This study established a method to quantify the changes of intra-radicular alveolar bone in the posterior maxilla in an accepted rat osteoporosis model. The degree of the osteoporotic changes to trabecular bone architecture is site-dependent and at least 3 months are required for the osteoporotic effects to be apparent in the posterior maxilla following rat OVX.

An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).