Talking about watching : using the video card game and wiki-web technology to engage IT students in developing observational skills.

Designers need to develop good observational skills in order to conduct user studies that reveal the subtleties of human interactions and adequately inform design activity. In this paper we describe a game format that we have used in concert with wiki-web technology, to engage our IT and Information Environments students in developing much sharper observational skills. The Video Card Game is a method of video analysis that is suited to design practitioners as well as to researchers. It uses the familiar format of a card game similar to "Happy Families,, to help students develop themes of interactions from watching video clips. Students then post their interaction themes on wiki-web pages, which allows the teaching team and other students to edit and comment on them. We found that the tangible (cards), game, role playing and sharing aspects of this method led to a much larger amount of interaction and discussion between student groups and between students and the teaching team, than we have achieved using our traditional teaching methods, while taking no more time on the part of the teaching staff. The quality of the resulting interaction themes indicates that this method fosters development of observational skills.In the paper we describe the motivations, method and results in full. We also describe the research context in which we collected the videotape data, and how this method relates to state of the art research methods in interaction design for ubiquitous computing technology.

Lawful withdrawal: The video

When should a person who has a heart attack not be resuscitated? When should a patient no longer be kept alive on a ventilator, or be provided with food and water by a tube? When should a person not be given a blood transfusion they need to stay alive? The answers to these questions depend on a number of factors including the mental or physical condition of the patient and any wishes they have expressed prior to losing the ability to make this decision, as well as the requirements of good medical practice. This video is a record of a public lecture held on 7 July 2004 by the Faculty of Law at the Queensland University of Technology, in association with the Faculty of Health, the Centre for Palliative Care Research and Education, and Palliative Care Queensland.

Brand placements in computer and video games : an overview and research questions

Despite the size and growth of the computer and video gaming industry – as well as the increasing use of the medium for the placement of advertising and product placement – researchers have neglected this area. By drawing on existing literature and research in similar and related areas of film product placement, sponsorship and interactivity, the authors present a conceptual overview and identify areas for research.

A review of the video games industry in the United States

With increasing revenues for video game manufacturers, higher software sales and a more diverse audience, the video games industry has been experiencing strong and rapid growth in recent times, rivalling other forms of entertainment. As a result, games have begun to attract the attention of marketing practitioners who are finding it increasingly difficult to attract consumer attention, and are seeking alternative media for marketing communications. This paper provides a review of the video games industry in the United States and raises the question as to whether games are a viable new medium for marketing messages. Areas for research are identified.

Exploring product placement in video games : an investigation of recall effects

Despite its growth and prominence, product placement is generally under-researched and this is even more apparent in the area of placement in video gaming. This paper presents exploratory focus group research into this practice. Findings indicate that the introductory footage to a game provides placement opportunities with the highest level of recall, while peripheral non-action is the worst. Interestingly, recall also appears to be higher for individual brands as opposed to manufacturer brands.

Digital media literacy : connecting young people’s identities, creative production and learning about video games

This chapter outlines examples of classroom activities that aim to make connections between young people’s everyday experiences with video games and the formal high school curriculum. These classroom activities were developed within the emerging field of digital media literacy. Digital media literacy combines elements of ‘traditional’ approaches to media education with elements of technology and information education (Buckingham, 2007; Warschauer, 2006). It is an educational field that has gained significant attention in recent years. For example, digital media literacy has become a significant objective for media policy makers in response to the increased social and cultural roles of new media technologies and controversies associated with young people’s largely unregulated online participation. Media regulators, educational institutions and independent organizations1 in the United States, Canada, the United Kingdom and Australia have developed digital media literacy initiatives that aim to provide advice to parents, teachers and young people.

Improved detection and tracking of objects in surveillance video

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

User-centered video quality assessment for scalable video coding of H.264/AVC standard

Scalable video coding of H.264/AVC standard enables adaptive and flexible delivery for multiple devices and various network conditions. Only a few works have addressed the influence of different scalability parameters (frame rate, spatial resolution, and SNR) on the user perceived quality within a limited scope. In this paper, we have conducted an experiment of subjective quality assessment for video sequences encoded with H.264/SVC to gain a better understanding of the correlation between video content and UPQ at all scalable layers and the impact of rate-distortion method and different scalabilities on bitrate and UPQ. Findings from this experiment will contribute to a user-centered design of adaptive delivery of scalable video stream.

Automatic tracking, super-resolution and recognition of human faces from surveillance video

Identifying an individual from surveillance video is a difficult, time consuming and labour intensive process. The proposed system aims to streamline this process by filtering out unwanted scenes and enhancing an individual's face through super-resolution. An automatic face recognition system is then used to identify the subject or present the human operator with likely matches from a database. A person tracker is used to speed up the subject detection and super-resolution process by tracking moving subjects and cropping a region of interest around the subject's face to reduce the number and size of the image frames to be super-resolved respectively. In this paper, experiments have been conducted to demonstrate how the optical flow super-resolution method used improves surveillance imagery for visual inspection as well as automatic face recognition on an Eigenface and Elastic Bunch Graph Matching system. The optical flow based method has also been benchmarked against the ``hallucination'' algorithm, interpolation methods and the original low-resolution images. Results show that both super-resolution algorithms improved recognition rates significantly. Although the hallucination method resulted in slightly higher recognition rates, the optical flow method produced less artifacts and more visually correct images suitable for human consumption.