Online video in education : acquisition, value & ROI

The session explores the potential for “Patron Driven Acquisition” (PDA) as a model for the acquisition of online video. Today, PDA has become a standard model of acquisition in the eBook market, more effectively aligning spend with use and increased return on investment (ROI). PDA is an unexplored model for acquisition of video, for which library collection development is complicated by higher storage and delivery costs, labor overheads for content selection and acquisition, and a dynamic film industry in which media and the technology that supports it is changing daily. Queensland University of Technology (QUT) and La Trobe University in Australia launched a research project in collaboration with Kanopy to explore the opportunity for PDA of video. The study relied on three data sources: (1) national surveys to compare the video purchasing and use practices of colleges, (2) on-campus pilot projects of PDA models to assess user engagement and behavior, and (3) testing of various user applications and features to support the model. The study incorporates usage statistics and survey data and builds upon a peer-reviewed research paper presented at the VALA 2014 conference in Melbourne, Australia. This session will be conducted by the researchers and will graphically present the results from the study. It will map out a future for video PDA, and how libraries can more cost-effectively acquire and maximize the discoverability of online video. The presenters will also solicit input and welcome questions from audience members.

Survey : video forensic tools

Due to extension of using CCTVs and the other video security systems in all areas, these sorts of devices have been introduced as the most important digital evidences to search and seizure crimes. Video forensics tools are developed as a part of digital forensics tools to analyze digital evidences and clear vague points of them for presenting in the courts Existing video forensics tools have been facilitated the investigation process by providing different features based on various video editing techniques. In this paper, some of the most popular video forensics tools are discussed and the strengths and shortages of them are compared and consequently, an alternative framework which includes the strengths of existing popular tools is introduced.

Defining the spatiotemporal surveillance space for alien species’ invasions using approximate Bayesian computation

The spatiotemporal dynamics of an alien species invasion across a real landscape are typically complex. While surveillance is an essential part of a management response, planning surveillance in space and time present a difficult challenge due to this complexity. We show here a method for determining the highest probability sites for occupancy across a landscape at an arbitrary point in the future, based on occupancy data from a single slice in time. We apply to the method to the invasion of Giant Hogweed, a serious weed in the Czech republic and throughout Europe.

Creative expression as the objective in video games

This study explores the idea of video games where the players are not just allowed to express themselves creatively, but are challenged to do so and are judged based on the quality of their creative expression. The outcome of the research is a series of six games which comment on this idea. The study also raises further questions regarding how current video games are constructed and designed in comparison with non-computer games, and invites a further evolution of the craft of video game design in a direction that focuses more on interpreting and reacting to what the player is doing.

World peace for video art

A single channel video projection with image, text and sound components. It was projected so as entirely fill a 3 x 3.5 wall in a 6 x 3.5 metre gallery space. The work deals with the role of humour and the fictocritical in exploring the relationship between politics and art.

Surviving the electronic panopticon: New lessons in democracy, surveillance, and community in young adult fiction

The ability of new information and communication technologies to pierce previously impenetrable physical, personal, and social boundaries has particular relevance to contemporary society and young people as there is now more information that can be collected, accessed, and distributed about individuals and groups. The ability to know about each other has become a central feature of many young people’s lives. The need to know is further complicated by other questions – Who knows? What do they know? What are the implications of this knowledge?. These questions are a consequence of society having become more mobile and networked enabling increased surveillance, tracking, and spreading of dis/information. With the acceleration of new pervasive and immersive technologies, these questions have taken on a new urgency and significance that go beyond an Orwellian Big Brother scenario. This chapter extends Foucault’s notion of the panopticon to take account of the challenges of an AmI environment of smart networked devices. By drawing on examples of recent young adult fiction, I examine some of the ways in which these texts invite their readers to reflect and speculate on the uneasy relationship between surveillance and democracy and what this means for individual rights and freedom, and a sense of place and belonging.

Acceptability-based QoE management for user-centric mobile video delivery : a field study evaluation

Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

Human identification from video using advanced gait recognition techniques

The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.

Towards pose-robust face recognition on video

This thesis investigates face recognition in video under the presence of large pose variations. It proposes a solution that performs simultaneous detection of facial landmarks and head poses across large pose variations, employs discriminative modelling of feature distributions of faces with varying poses, and applies fusion of multiple classifiers to pose-mismatch recognition. Experiments on several benchmark datasets have demonstrated that improved performance is achieved using the proposed solution.

Healthcare-associated infections in Australia : time for national surveillance

Abstract Objective. Healthcare-associated infection (HAI) surveillance programs are critical for infection prevention. Australia does not have a comprehensive national HAI surveillance program. The purpose of this paper is to provide an overview of established international and Australian statewide HAI surveillance programs and recommend a pathway for the development of a national HAI surveillance program in Australia. Methods. This study examined existing HAI surveillance programs through a literature review, a review of HAI surveillance program documentation, such as websites, surveillance manuals and data reports and direct contact with program representatives. Results. Evidence from international programs demonstrates national HAI surveillance reduces the incidence of HAIs. However, the current status of HAI surveillance activity in Australian states is disparate, variation between programs is not well understood, and the quality of data currently used to compose national HAI rates is uncertain. Conclusions. There is a need to develop a well-structured, evidence-based national HAI program in Australia to meet the increasing demand for validated reliable national HAI data. Such a program could be leveraged off the work of existing Australian and international programs.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Piecing the puzzle together : enhancing the quality of road trauma surveillance through linkage of police and health data

This program of research linked police and health data collections to investigate the potential benefits for road safety in terms of enhancing the quality of data. This research has important implications for road safety because, although police collected data has historically underpinned efforts in the area, it is known that many road crashes are not reported to police and that these data lack specific injury severity information. This research shows that data linkage provides a more accurate quantification of the severity and prevalence of road crash injuries which is essential for: prioritising funding; targeting interventions; and estimating the burden and cost of road trauma.