7,658 research outputs found

    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

    Automatic Synchronization of Multi-User Photo Galleries

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    In this paper we address the issue of photo galleries synchronization, where pictures related to the same event are collected by different users. Existing solutions to address the problem are usually based on unrealistic assumptions, like time consistency across photo galleries, and often heavily rely on heuristics, limiting therefore the applicability to real-world scenarios. We propose a solution that achieves better generalization performance for the synchronization task compared to the available literature. The method is characterized by three stages: at first, deep convolutional neural network features are used to assess the visual similarity among the photos; then, pairs of similar photos are detected across different galleries and used to construct a graph; eventually, a probabilistic graphical model is used to estimate the temporal offset of each pair of galleries, by traversing the minimum spanning tree extracted from this graph. The experimental evaluation is conducted on four publicly available datasets covering different types of events, demonstrating the strength of our proposed method. A thorough discussion of the obtained results is provided for a critical assessment of the quality in synchronization.Comment: ACCEPTED to IEEE Transactions on Multimedi

    Operating-system support for distributed multimedia

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    Multimedia applications place new demands upon processors, networks and operating systems. While some network designers, through ATM for example, have considered revolutionary approaches to supporting multimedia, the same cannot be said for operating systems designers. Most work is evolutionary in nature, attempting to identify additional features that can be added to existing systems to support multimedia. Here we describe the Pegasus project's attempt to build an integrated hardware and operating system environment from\ud the ground up specifically targeted towards multimedia

    Verifying service continuity in a satellite reconfiguration procedure: application to a satellite

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    The paper discusses the use of the TURTLE UML profile to model and verify service continuity during dynamic reconfiguration of embedded software, and space-based telecommunication software in particular. TURTLE extends UML class diagrams with composition operators, and activity diagrams with temporal operators. Translating TURTLE to the formal description technique RT-LOTOS gives the profile a formal semantics and makes it possible to reuse verification techniques implemented by the RTL, the RT-LOTOS toolkit developed at LAAS-CNRS. The paper proposes a modeling and formal validation methodology based on TURTLE and RTL, and discusses its application to a payload software application in charge of an embedded packet switch. The paper demonstrates the benefits of using TURTLE to prove service continuity for dynamic reconfiguration of embedded software

    Quality of experience study for multiple sensorial media delivery

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    Traditional video sequences make use of both visual images and audio tracks which are perceived by human eyes and ears, respectively. In order to present better ultra-reality virtual experience, the comprehensive human sensations (e.g. olfaction, haptic, gustatory, etc) needed to be exploited. In this paper, a multiple sensorial media (mulsemedia) delivery system is introduced to deliver multimedia sequences integrated with multiple media components which engage three or more of human senses such as sight, hearing, olfaction, haptic, gustatory, etc. Three sensorial effects (i.e. haptic, olfaction, and air-flowing) are selected for the purpose of demonstration. Subjective test is conducted to analyze the user perceived quality of experience of the mulsemedia service. It is concluded that the mulsemedia sequences can partly mask the decreased movie quality. Additionally the most preferable sensorial effect is haptic, followed by air-flowing and olfaction.This work was supported in part by Enterprise Ireland Innovation Partnership programme
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