36 resultados para video quality assessment
em Queensland University of Technology - ePrints Archive
Resumo:
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.
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This study constructs performance prediction models to estimate the end-user perceived video quality on mobile devices for the latest video encoding techniques –VP9 and H.265. Both subjective and objective video quality assessments were carried out for collecting data and selecting the most desirable predictors. Using statistical regression, two models were generated to achieve 94.5% and 91.5% of prediction accuracies respectively, depending on whether the predictor derived from the objective assessment is involved. These proposed models can be directly used by media industries for video quality estimation, and will ultimately help them to ensure a positive end-user quality of experience on future mobile devices after the adaptation of the latest video encoding technologies.
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In the age of climate change and rapid urbanisation, stormwater management and water sensitive urban design have become important issues for urban policy makers. This paper reports the initial findings of a research study that develops an indexing model for assessing stormwater quality in the Gold Coast.
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This paper presents a comprehensive study to find the most efficient bitrate requirement to deliver mobile video that optimizes bandwidth, while at the same time maintains good user viewing experience. In the study, forty participants were asked to choose the lowest quality video that would still provide for a comfortable and long-term viewing experience, knowing that higher video quality is more expensive and bandwidth intensive. This paper proposes the lowest pleasing bitrates and corresponding encoding parameters for five different content types: cartoon, movie, music, news and sports. It also explores how the lowest pleasing quality is influenced by content type, image resolution, bitrate, and user gender, prior viewing experience, and preference. In addition, it analyzes the trajectory of users’ progression while selecting the lowest pleasing quality. The findings reveal that the lowest bitrate requirement for a pleasing viewing experience is much higher than that of the lowest acceptable quality. Users’ criteria for the lowest pleasing video quality are related to the video’s content features, as well as its usage purpose and the user’s personal preferences. These findings can provide video providers guidance on what quality they should offer to please mobile users.
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Welcome to the Quality assessment matrix. This matrix is designed for highly qualified discipline experts to evaluate their course, major or unit in a systematic manner. The primary purpose of the Quality assessment matrix is to provide a tool that a group of academic staff at universities can collaboratively review the assessment within a course, major or unit annually. The annual review will result in you being read for an external curricula review at any point in time. This tool is designed for use in a workshop format with one, two or more academic staff, and will lead to an action plan for implementation.
Resumo:
Service bundles, in the context of e-government, are used to group services together that relate to a certain citizen need. These bundles can then be presented on a governmental one-stop portal to structure the available service offerings according to citizen expectations. In order to ensure that citizens utilise the one-stop portal and comprised service bundles for future transactions, the quality of these service bundles needs to be managed and maximised accordingly. Consequently, models and tools that focus on assessing service bundle quality play an important role, when it comes to increasing or retaining usage behaviour of citizens. This study focuses on providing a rigorous and structured literature review of e-government outlets with regards to their coverage of service bundle quality and e-service quality themes. The study contributes to academia and practice by providing a framework that allows structuring and classifying existing studies relevant for the assessment of quality for government portals. Furthermore, this study provides insights into the status quo of quality models that can be used by governments to assess the quality of their service bundles. Directions for future research and limitations of the present study are provided as well.
Resumo:
Quality of experience (QoE) measures the overall perceived quality of mobile video delivery from subjective user experience and objective system performance. Current QoE computing models have two main limitations: 1) insufficient consideration of the factors influencing QoE, and; 2) limited studies on QoE models for acceptability prediction. In this paper, a set of novel acceptability-based QoE models, denoted as A-QoE, is proposed based on the results of comprehensive user studies on subjective quality acceptance assessments. The models are able to predict users’ acceptability and pleasantness in various mobile video usage scenarios. Statistical regression analysis has been used to build the models with a group of influencing factors as independent predictors, including encoding parameters and bitrate, video content characteristics, and mobile device display resolution. The performance of the proposed A-QoE models has been compared with three well-known objective Video Quality Assessment metrics: PSNR, SSIM and VQM. The proposed A-QoE models have high prediction accuracy and usage flexibility. Future user-centred mobile video delivery systems can benefit from applying the proposed QoE-based management to optimize video coding and quality delivery decisions.
Resumo:
Current mobile devices and streaming video services support high definition (HD) video, increasing expectation for more contents. HD video streaming generally requires large bandwidth, exerting pressures on existing networks. New generation of video compression codecs, such as VP9 and H.265/HEVC, are expected to be more effective for reducing bandwidth. Existing studies to measure the impact of its compression on users’ perceived quality have not been focused on mobile devices. Here we propose new Quality of Experience (QoE) models that consider both subjective and objective assessments of mobile video quality. We introduce novel predictors, such as the correlations between video resolution and size of coding unit, and achieve a high goodness-of-fit to the collected subjective assessment data (adjusted R-square >83%). The performance analysis shows that H.265 can potentially achieve 44% to 59% bit rate saving compared to H.264/AVC, slightly better than VP9 at 33% to 53%, depending on video content and resolution.
Resumo:
The increase of powerful mobile devices has accelerated the demand for mobile videos. Previous studies in mobile video have focused on understanding of mobile video usage, improvement of video quality, and user interface design in video browsing. However, research focusing on a deep understanding of users’ needs for a pleasing quality delivery of mobile video is lacking. In particular, what quality-delivery mode users prefer and what information relevant to video quality they need requires attention. This paper presents a qualitative interview study with 38 participants to gain an insight into three aspects: influencing factors of user-desired video quality, user-preferred quality-delivery modes, and user-required interaction information of mobile video. The results show that user requirements for video quality are related to personal preference, technology background and video viewing experience, and the preferred quality-delivery mode and interactive mode are diverse. These complex user requirements call for flexible and personalised quality delivery and interaction of mobile video.
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This paper considers the conditions that are necessary at system and local levels for teacher assessment to be valid, reliable and rigorous. With sustainable assessment cultures as a goal, the paper examines how education systems can support local level efforts for quality learning and dependable teacher assessment. This is achieved through discussion of relevant research and consideration of a case study involving an evaluation of a cross-sectoral approach to promoting confidence in school-based assessment in Queensland, Australia. Building on the reported case study, essential characteristics for developing sustainable assessment cultures are presented, including: leadership in learning; alignment of curriculum, pedagogy and assessment; the design of quality assessment tasks and accompanying standards, and evidence-based judgement and moderation. Taken together, these elements constitute a new framework for building assessment capabilities and promoting quality assurance.
Resumo:
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.
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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.
Resumo:
- Considers broad-scale assessment approaches and how they impact on educational opportunity and outcomes. - Brings together internationally recognised scholars providing new insights into assessment for learning improvement and accountability. - Presents different theoretical and methodological perspectives influential in the field of assessment, learning and social change. - Contributes to the theorising of assessment in contexts characterised by heightened accountability requirements and constant change. This book brings together internationally recognised scholars with an interest in how to use the power of assessment to improve student learning and to engage with accountability priorities at both national and global levels. It includes distinguished writers who have worked together for some two decades to shift the assessment paradigm from a dominant focus on assessment as measurement towards assessment as central to efforts to improve learning. These writers have worked with the teaching profession and, in so doing, have researched and generated key insights into different ways of understanding assessment and its relationship to learning. The volume contributes to the theorising of assessment in contexts characterised by heightened accountability requirements and constant change. The book’s structure and content reflect already significant and growing international interest in assessment as contextualised practice, as well as theories of learning and teaching that underpin and drive particular assessment approaches. Learning theories and practices, assessment literacies, teachers’ responsibilities in assessment, the role of leadership, and assessment futures are the organisers within the book’s structure and content. The contributors to this book have in common the view that quality assessment, and quality learning and teaching are integrally related. Another shared view is that the alignment of assessment with curriculum, teaching and learning is linchpin to efforts to improve both learning opportunities and outcomes for all. Essentially, the book presents new perspectives on the enabling power of assessment. In so doing, the writers recognise that validity and reliability - the traditional canons of assessment – remain foundational and therefore necessary. However, they are not of themselves sufficient for quality education. The book argues that assessment needs to be radically reconsidered in the context of unprecedented societal change. Increasingly, communities are segregating more by wealth, with clear signs of social, political, economic and environmental instability. These changes raise important issues relating to ethics and equity, taken to be core dimensions in enabling the power of assessment to contribute to quality learning for all. This book offers readers new knowledge about how assessment can be used to re/engage learners across all phases of education.