Building the computer mediated distance learning community: Issues and observations drawn from teaching and learning

This paper discusses computer mediated distance learning on a Master's level course in the UK and student perceptions of this as a quality learning environment.

Improving level crossing safety through enhanced data recording and reporting : The CRC for Rail Innovation’s Baseline Rail Level Crossing Video project

This paper describes the work being conducted in the baseline rail level crossing project, supported by the Australian rail industry and the Cooperative Research Centre for Rail Innovation. The paper discusses the limitations of near-miss data for analysis obtained using current level crossing occurrence reporting practices. The project is addressing these limitations through the development of a data collection and analysis system with an underlying level crossing accident causation model. An overview of the methodology and improved data recording process are described. The paper concludes with a brief discussion of benefits this project is expected to provide the Australian rail industry.

Detecting anomalous events at railway level crossings

Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

Transitioning from dependent to more independent learners : Using video tutorials as a means of helping students help themselves

This paper examines the use of short video tutorials in a post-graduate accounting subject, as a means of helping students transition from dependent to more independent learners. Five short (three to five minute) video tutorials were introduced in an effort to shift the reliance for learning from the lecturer to the student. Students’ usage of video tutorials, comments by students, and reliance on teaching staff for individual assistance were monitored over three semesters from 2008 to 2009. Interviews with students were then conducted in late 2009 to more comprehensively evaluate the use and benefits of video tutorials. Findings reveal preliminary but positive outcomes in terms of both more efficient teaching and more effective learning.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

User-centred study on quality of mobile video services

Mobile video, as an emerging market and a promising research field, has attracted much attention from both industry and researchers. Considering the quality of user-experience as the crux of mobile video services, this chapter aims to provide a guide to user-centered studies of mobile video quality. This will benefit future research in better understanding user needs and experiences, designing effective research, and providing solid solutions to improve the quality of mobile video. This chapter is organized in three main parts: (1) a review of recent user studies from the perspectives of research focuses, user study methods, and data analysis methods; (2) an example of conducting a user study of mobile video research, together with the discussion on a series of relative issues, such as participants, materials and devices, study procedure, and analysis results, and; (3) a conclusion with an open discussion about challenges and opportunities in mobile video related research, and associated potential future improvements.

Get real : the development, implementation and evaluation of an intervention for primary aged children with High Functioning Autism

Children with Autism Spectrum Disorder experience difficulty in communication and in understanding the social world which can have negative consequences for their relationships, in managing emotions, and generally dealing with the challenges of everyday life. This thesis examines the effectiveness of the Active and Reflective components of the Get REAL program through the assessment of the detailed coding of video-recorded observations and longitudinal quantitative analysis. The aim of Get REAL is to increase the social, emotional, and cognitive learning of children with High Functioning Autism (HFA). Get REAL is a group program designed specifically for use in inclusive primary school settings. The Get REAL program was designed in response to the mixed success of generalisation of learning to new contexts of existing social skills programs. The theoretical foundation of Get REAL is based upon pedagogical theory and learning theory to facilitate transfer of learning, combined with experiential, individualised, evaluative and organisational approaches. This thesis is by publication and consists of four refereed journal papers; 1 accepted for publication and 3 that are under review. Paper 1 describes the development and theoretical basis of the Get REAL program and provides detail of the program structure and learning cycle. The focus of Paper 1 reflects the first question of interest in the thesis which is about the extent to which learning derived from participation in the program can be generalised to other contexts. Participants are 16 children with HFA ranging in age from 8-13 years. Results provided support for the generalisability of learning from Get REAL to home and school evidenced by parent and teacher data collected pre and post participation in Get REAL. Following establishment of the generalisation of learning from Get REAL, Papers 2 and 3 focus on the Active and Reflective components of the program in order to examine how individual and group learning takes place. Participants (N = 12) in the program are video-taped during the Active and Reflective Sessions. Using identical coding protocols of video data, improvements in prosocial behaviour and diminishing of inappropriate behaviours were apparent with the exception of perspective taking. Data also revealed that 2 of the participants had atypical trajectories. An in-depth case study analysis was then conducted with these 2 participants in Paper 4. Data included reports from health care and education professionals within the school and externally (e.g., paediatrician) and identified the multi-faceted nature of care needed for children with comorbid diagnoses and extremely challenging family circumstances as a complex task to effect change. Results of this research support the effectiveness of the Get REAL program in promoting pro social behaviours such as improvements in engaging with others and emotional regulation, and in diminishing unwanted behaviours such as conduct problems. Further, the gains made by the participating children were found to be generalisable beyond Get REAL to home and other school settings. The research contained in the thesis adds to current knowledge about how learning can take place for children with HFA. Results show that an experiential learning framework with a focus on social cognition, together with explicit teaching, scaffolded with video feedback, are key ingredients for the generalisation of social learning to broader contexts.

Research capacity and culture in podiatry : early observations within Queensland Health

Background Research is a major driver of health care improvement and evidence-based practice is becoming the foundation of health care delivery. For health professions to develop within emerging models of health care delivery, it would seem imperative to develop and monitor the research capacity and evidence-based literacy of the health care workforce. This observational paper aims to report the research capacity levels of statewide populations of public-sector podiatrists at two different time points twelve-months apart. Methods The Research Capacity & Culture (RCC) survey was electronically distributed to all Queensland Health (Australia) employed podiatrists in January 2011 (n = 58) and January 2012 (n = 60). The RCC is a validated tool designed to measure indicators of research skill in health professionals. Participants rate skill levels against each individual, team and organisation statement on a 10-point scale (one = lowest, ten = highest). Chi-squared and Mann Whitney U tests were used to determine any differences between the results of the two survey samples. A minimum significance of p < 0.05 was used throughout. Results Thirty-seven (64%) podiatrists responded to the 2011 survey and 33 (55%) the 2012 survey. The 2011 survey respondents reported low skill levels (Median < 4) on most aspects of individual research aspects, except for their ability to locate and critically review research literature (Median > 6). Whereas, most reported their organisation’s skills to perform and support research at much higher levels (Median > 6). The 2012 survey respondents reported significantly higher skill ratings compared to the 2011 survey in individuals’ ability to secure research funding, submit ethics applications, and provide research advice, plus, in their organisation’s skills to support, fund, monitor, mentor and engage universities to partner their research (p < 0.05). Conclusions This study appears to report the research capacity levels of the largest populations of podiatrists published. The 2011 survey findings indicate podiatrists have similarly low research capacity skill levels to those reported in the allied health literature. The 2012 survey, compared to the 2011 survey, suggests podiatrists perceived higher skills and support to initiate research in 2012. This improvement coincided with the implementation of research capacity building strategies.

Perspectives on schooling from early adolescent video diaries

The aim of this project was to gain the voice of the early adolescent (aged between 11 and 13 years) about the things that are genuinely important to them in their lives. Eight participants were asked to record a private video diary entry each night for one week. A number of thematic topics were identified including: their experiences and perspectives on school curriculum and assessment, opinions about schooling structures, and importance of friendship and family. Giving young adolescents the opportunity to voice their opinions has been valuable in gaining insight to the relative impacts of teaching and learning approaches in their school contexts and the issues they consider as the most important in their lives.

A framework of Dynamic Difficulty Adjustment in competitive multiplayer video games

The balance between player competence and the challenge presented by a task has been acknowledged as a major factor in providing optimal experience in video games. While Dynamic Difficulty Adjustment (DDA) presents methods for adjusting difficulty in real-time during singleplayer games, little research has explored its application in competitive multiplayer games where challenge is dictated by the competence of human opponents. By conducting a formal review of 180 existing competitive multiplayer games, it was found that a large number of modern games are utilizing DDA techniques to balance challenge between human opponents. From this data, we propose a preliminary framework for classifying Multiplayer Dynamic Difficulty Adjustment (mDDA) instances.

Real-time video event detection in crowded scenes using MPEG derived features : a multiple instance learning approach

This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.

Nonrigid face alignment for unknown subject in video

Non-rigid face alignment is a very important task in a large range of applications but the existing tracking based non-rigid face alignment methods are either inaccurate or requiring person-specific model. This dissertation has developed simultaneous alignment algorithms that overcome these constraints and provide alignment with high accuracy, efficiency, robustness to varying image condition, and requirement of only generic model.

Clinical skin examination outcomes after a video-based behavioral intervention analysis from a randomized clinical trial

Importance Older men are at risk of dying of melanoma. Objective To assess attendance at and clinical outcomes of clinical skin examinations (CSEs) in older men exposed to a video-based behavioral intervention. Design, Setting, and Participants This was a behavioral randomized clinical trial of a video-based intervention in men aged at least 50 years. Between June 1 and August 31, 2008, men were recruited, completed baseline telephone interviews, and were than randomized to receive either a video-based intervention (n = 469) or brochures only (n = 461; overall response rate, 37.1%) and were again interviewed 7 months later (n = 870; 93.5% retention). Interventions Video on skin self-examination and skin awareness and written informational materials. The control group received written materials only. Main Outcomes and Measures Participants who reported a CSE were asked for the type of CSE (skin spot, partial body, or whole body), who initiated it, whether the physician noted any suspicious lesions, and, if so, how lesions were managed. Physicians completed a case report form that included the type of CSE, who initiated it, the number of suspicious lesions detected, how lesions were managed (excision, nonsurgical treatment, monitoring, or referral), and pathology reports after lesion excision or biopsy. Results Overall, 540 of 870 men (62.1%) self-reported a CSE since receiving intervention materials, and 321 of 540 (59.4%) consented for their physician to provide medical information (received for 266 of 321 [82.9%]). Attendance of any CSE was similar between groups (intervention group, 246 of 436 [56.4%]; control group, 229 of 434 [52.8%]), but men in the intervention group were more likely to self-report a whole-body CSE (154 of 436 [35.3%] vs 118 of 434 [27.2%] for control group; P = .01). Two melanomas, 29 squamous cell carcinomas, and 38 basal cell carcinomas were diagnosed, with a higher proportion of malignant lesions in the intervention group (60.0% vs 40.0% for controls; P = .03). Baseline attitudes, behaviors, and skin cancer history were associated with higher odds of CSE and skin cancer diagnosis. Conclusions and Relevance A video-based intervention may increase whole-body CSE and skin cancer diagnosis in older men. Trial Registration: anzctr.org.au Identifier: ACTRN12608000384358

Carrot red leaf and carrot mottle viruses : observations on the composition of the particles in single and mixed infections

Particles of carrot red leaf virus (CRLV; luteovirus group) purified from chervil (Anthriscus cerefolium) contain a single ssRNA species of mol. wt. about 1.8 x 106 and a major protein of mol. wt. about 25000. CRLV acts as a helper for aphid transmission of carrot mottle virus (CMotV; ungrouped) from mixedly infected plants. Virus preparations purified from such plants possess the infectivity of both viruses but contain particles indistinguishable from those of CRLV; some of the particles are therefore thought to consist of CMotV RNA packaged in CRLV coat protein. When RNA from such preparations was electrophoresed in agarose/polyacrylamide gels, CMotV infectivity was associated with an RNA band that migrated ahead of the CRLV RNA band and had an estimated mol. wt. of about 1.5 x 106, similar to that previously found for the infective ssRNA extracted directly from Nicotiana clevelandii leaves infected with CMotV alone. Preparations of dsRNA from CMotV-infected N. clevelandii leaves contained two species: one of mol. wt. about 3.2 x 106, presumably the replicative form of the infective ssRNA, and the other, mol. wt. about 0.9 x 106, of unknown origin and function. The infective agent in buffer extracts of CMotV-infected N. clevelandii was resistant to RNase (although the enzyme acted as a reversible inhibitor of infection at high concentrations) and is therefore not unprotected RNA. It may be protected within the approximately 52 nm enveloped structures previously reported.

Quality based frame selection for face clustering in news video

Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.