13,898 research outputs found

    Objective assessment of region of interest-aware adaptive multimedia streaming quality

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    Adaptive multimedia streaming relies on controlled adjustment of content bitrate and consequent video quality variation in order to meet the bandwidth constraints of the communication link used for content delivery to the end-user. The values of the easy to measure network-related Quality of Service metrics have no direct relationship with the way moving images are perceived by the human viewer. Consequently variations in the video stream bitrate are not clearly linked to similar variation in the user perceived quality. This is especially true if some human visual system-based adaptation techniques are employed. As research has shown, there are certain image regions in each frame of a video sequence on which the users are more interested than in the others. This paper presents the Region of Interest-based Adaptive Scheme (ROIAS) which adjusts differently the regions within each frame of the streamed multimedia content based on the user interest in them. ROIAS is presented and discussed in terms of the adjustment algorithms employed and their impact on the human perceived video quality. Comparisons with existing approaches, including a constant quality adaptation scheme across the whole frame area, are performed employing two objective metrics which estimate user perceived video quality

    Random Linear Network Coding for 5G Mobile Video Delivery

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    An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio

    Managing evolution and change in web-based teaching and learning environments

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    The state of the art in information technology and educational technologies is evolving constantly. Courses taught are subject to constant change from organisational and subject-specific reasons. Evolution and change affect educators and developers of computer-based teaching and learning environments alike – both often being unprepared to respond effectively. A large number of educational systems are designed and developed without change and evolution in mind. We will present our approach to the design and maintenance of these systems in rapidly evolving environments and illustrate the consequences of evolution and change for these systems and for the educators and developers responsible for their implementation and deployment. We discuss various factors of change, illustrated by a Web-based virtual course, with the objective of raising an awareness of this issue of evolution and change in computer-supported teaching and learning environments. This discussion leads towards the establishment of a development and management framework for teaching and learning systems

    Beyond multimedia adaptation: Quality of experience-aware multi-sensorial media delivery

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    Multiple sensorial media (mulsemedia) combines multiple media elements which engage three or more of human senses, and as most other media content, requires support for delivery over the existing networks. This paper proposes an adaptive mulsemedia framework (ADAMS) for delivering scalable video and sensorial data to users. Unlike existing two-dimensional joint source-channel adaptation solutions for video streaming, the ADAMS framework includes three joint adaptation dimensions: video source, sensorial source, and network optimization. Using an MPEG-7 description scheme, ADAMS recommends the integration of multiple sensorial effects (i.e., haptic, olfaction, air motion, etc.) as metadata into multimedia streams. ADAMS design includes both coarse- and fine-grained adaptation modules on the server side: mulsemedia flow adaptation and packet priority scheduling. Feedback from subjective quality evaluation and network conditions is used to develop the two modules. Subjective evaluation investigated users' enjoyment levels when exposed to mulsemedia and multimedia sequences, respectively and to study users' preference levels of some sensorial effects in the context of mulsemedia sequences with video components at different quality levels. Results of the subjective study inform guidelines for an adaptive strategy that selects the optimal combination for video segments and sensorial data for a given bandwidth constraint and user requirement. User perceptual tests show how ADAMS outperforms existing multimedia delivery solutions in terms of both user perceived quality and user enjoyment during adaptive streaming of various mulsemedia content. In doing so, it highlights the case for tailored, adaptive mulsemedia delivery over traditional multimedia adaptive transport mechanisms
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