Video-based training combined with flotation tank recovery does not improve three-point shooting in basketball

Video-based training combined with flotation tank recovery may provide an additional stimulus for improving shooting in basketball. A pre-post controlled trial was conducted to assess the effectiveness of a 3 wk intervention combining video-based training and flotation tank recovery on three-point shooting performance in elite female basketball players. Players were assigned to an experimental (n=10) and control group (n=9). A 3 wk intervention consisted of 2 x 30 min float sessions a week which included 10 min of video-based training footage, followed by a 3 wk retention phase. A total of 100 three-point shots were taken from 5 designated positions on the court at each week to assess three-point shooting performance. There was no clear difference in the mean change in the number of successful three-point shots between the groups (-3%; ±18%, mean; ±90% confidence limits). Video-based training combined with flotation recovery had little effect on three-point shooting performance.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

User-driven quality of experience modelling for mobile video optimisation

The increasing demand for mobile video has attracted much attention from both industry and researchers. To satisfy users and to facilitate the usage of mobile video, providing optimal quality to the users is necessary. As a result, quality of experience (QoE) becomes an important focus in measuring the overall quality perceived by the end-users, from the aspects of both objective system performance and subjective experience. However, due to the complexity of user experience and diversity of resources (such as videos, networks and mobile devices), it is still challenging to develop QoE models for mobile video that can represent how user-perceived value varies with changing conditions. Previous QoE modelling research has two main limitations: aspects influencing QoE are insufficiently considered; and acceptability as the user value is seldom studied. Focusing on the QoE modelling issues, two aims are defined in this thesis: (i) investigating the key influencing factors of mobile video QoE; and (ii) establishing QoE prediction models based on the relationships between user acceptability and the influencing factors, in order to help provide optimal mobile video quality. To achieve the first goal, a comprehensive user study was conducted. It investigated the main impacts on user acceptance: video encoding parameters such as quantization parameter, spatial resolution, frame rate, and encoding bitrate; video content type; mobile device display resolution; and user profiles including gender, preference for video content, and prior viewing experience. Results from both quantitative and qualitative analysis revealed the significance of these factors, as well as how and why they influenced user acceptance of mobile video quality. Based on the results of the user study, statistical techniques were used to generate a set of QoE models that predict the subjective acceptability of mobile video quality by using a group of the measurable influencing factors, including encoding parameters and bitrate, content type, and mobile device display resolution. Applying the proposed QoE models into a mobile video delivery system, optimal decisions can be made for determining proper video coding parameters and for delivering most suitable quality to users. This would lead to consistent user experience on different mobile video content and efficient resource allocation. The findings in this research enhance the understanding of user experience in the field of mobile video, which will benefit mobile video design and research. This thesis presents a way of modelling QoE by emphasising user acceptability of mobile video quality, which provides a strong connection between technical parameters and user-desired quality. Managing QoE based on acceptability promises the potential for adapting to the resource limitations and achieving an optimal QoE in the provision of mobile video content.

Video-based road commentary training improves hazard perception of young drivers in a dual task

This study used a video-based hazard perception dual task to compare the hazard perception skills of young drivers with middle aged, more experienced drivers and to determine if these skills can be improved with video-based road commentary training. The primary task required the participants to detect and verbally identify immediate hazard on video-based traffic scenarios while concurrently performing a secondary tracking task, simulating the steering of real driving. The results showed that the young drivers perceived fewer immediate hazards (mean = 75.2%, n = 24, 19 females) than the more experienced drivers (mean = 87.5%, n = 8, all females), and had longer hazard perception times, but performed better in the secondary tracking task. After the road commentary training, the mean percentage of hazards detected and identified by the young drivers improved to the level of the experienced drivers and was significantly higher than that of an age and driving experience matched control group. The results will be discussed in the context of psychological theories of hazard perception and in relation to road commentary as an evidence-based training intervention that seems to improve many aspects of unsafe driving behaviour in young drivers.

Personality & video game genre preferences

This research has been conducted to ascertain whether people with certain personality types exhibit preferences for particular game genres. Four hundred and sixty-six participants completed an online survey in which they described their preference for various game genres and provided measures of personality. Personality types were measured using the five-factor model of personality. Significant relationships between personality types and game genres were found. The results are interpreted in the context of the features of particular game genres and possible matches between personality traits and these features.

Personality, motivation and video games

This study explored relationships between personality, video game preference and gaming experiences. Two hundred and thirty-five participants completed an online survey in which they recalled a recent gaming experience, and provided measures of personality and their gaming experience via the Player Experience of Need Satisfaction (PENS) measure. Relationships between game genre, personality and gaming experience were found. Results are interpreted with reference to the validity of the PENS, current models of video gaming motivations and enjoyment, and sub-groups of people that may be more vulnerable to possible negative effects of games.

AR Services Video

Video presented as part of the USECA 2011 workshop at WISE 2011. Real-time sales assistant service is a problematic component of remote delivery of sales support for customers. Solutions involving web pages, telephony and video support prove problematic when seeking to remotely guide customers in their sales processes, especially with transactions revolving around physically complex artefacts. This process involves a number of services that are often complex in nature, ranging from physical compatibility and configuration factors, to availability and credit services. We propose the application of a combination of virtual worlds and augmented reality to create synthetic environments suitable for remote sales of physical artefacts, right in the home of the purchaser. A high level description of the service structure involved is shown, along with a use case involving the sale of electronic goods and services within an example augmented reality application. We expect this work to have application in many sales domains involving physical objects needing to be sold over the Internet.

Changing tastes in food media : a study of recipe sharing traditions in the food blogging community

Food is inherently cultural yet traditionally overlooked in many disciplines as a topic worthy of serious investigation. This thesis investigates how food, as a topic of interest, is thriving in an online environment through recipe sharing on food blogs. It applies an ethnographic approach to online community studies, providing a rich description of the food blogging community. The thesis demonstrates how the food blogging can be seen as a community. Through a case study focusing on a one recipe shared across many blogs, it also examines the community in action. As the community has grown, it has become more complex, structured and diverse. The thesis examines its evolution and the response of food-related media and other industries to food blogging. The nature of the food blogging community reflects the cultural and social nature of food and the ongoing evolution of recipe sharing through food-related media. Food blogs provide an insight into the eating habits of ‘ordinary’ people, in a more broad-based manner than traditional food-related media such as cookbooks. Beyond this, food blogs are part of wider cultural trends towards DIY, and provide a useful example of the ongoing transformation of food-related media, food culture, and indeed, culture more broadly.

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.

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.

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.