66 research outputs found

    Format-independent media resource adaptation and delivery

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    Cost of in-network adaption of MC-EZBC for universal multimedia access

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    Device-based decision-making for adaptation of three-dimensional content

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    The goal of this research was the creation of an adaptation mechanism for the delivery of three-dimensional content. The adaptation of content, for various network and terminal capabilities - as well as for different user preferences, is a key feature that needs to be investigated. Current state-of-the art research of the adaptation shows promising results for specific tasks and limited types of content, but is still not well-suited for massive heterogeneous environments. In this research, we present a method for transmitting adapted three-dimensional content to multiple target devices. This paper presents some theoretical and practical methods for adapting three-dimensional content, which includes shapes and animation. We also discuss practical details of the integration of our methods into MPEG-21 and MPEG-4 architecture

    CAIN-21: Automatic adaptation decisions and extensibility in an MPEG-21 adaptation engine

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    This paper presents the progress and final state of CAIN-21, an extensible and metadata driven multimedia adaptation in the MPEG-21 framework. CAIN-21 facilitates the integration of pluggable multimedia adaptation tools, automatically chooses the chain of adaptations to perform and manages its execution. To drive the adaptation, it uses the description tools and implied ontology established by MPEG-21. The paper not only describes the evolution and latest version of CAIN-21, but also identifies limitations and ambiguities in the description capabilities of MPEG-21. Therefore, it proposes some extensions to the MPEG-21 description schema for removing these problems. Finally, the pros and cons of CAIN-21 with respect to other multimedia adaptation engines are discussed

    Format-Independent Multimedia Streaming

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    Personalizing quality aspects for video communication in constrained heterogeneous environments

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    The world of multimedia communication is drastically evolving since a few years. Advanced compression formats for audiovisual information arise, new types of wired and wireless networks are developed, and a broad range of different types of devices capable of multimedia communication appear on the market. The era where multimedia applications available on the Internet were the exclusive domain of PC users has passed. The next generation multimedia applications will be characterized by heterogeneity: differences in terms of the networks, devices and user expectations. This heterogeneity causes some new challenges: transparent consumption of multimedia content is needed in order to be able to reach a broad audience. Recently, two important technologies have appeared that can assist in realizing such transparent Universal Multimedia Access. The first technology consists of new scalable or layered content representation schemes. Such schemes are needed in order to make it possible that a multimedia stream can be consumed by devices with different capabilities and transmitted over network connections with different characteristics. The second technology does not focus on the content representation itself, but rather on linking information about the content, so-called metadata, to the content itself. One of the possible uses of metadata is in the automatic selection and adaptation of multimedia presentations. This is one of the main goals of the MPEG-21 Multimedia Framework. Within the MPEG-21 standard, two formats were developed that can be used for bitstream descriptions. Such descriptions can act as an intermediate layer between a scalable bitstream and the adaptation process. This way, format-independent bitstream adaptation engines can be built. Furthermore, it is straightforward to add metadata information to the bitstream description, and use this information later on during the adaptation process. Because of the efforts spent on bitstream descriptions during our research, a lot of attention is devoted to this topic in this thesis. We describe both frameworks for bitstream descriptions that were standardized by MPEG. Furthermore, we focus on our own contributions in this domain: we developed a number of bitstream schemas and transformation examples for different types of multimedia content. The most important objective of this thesis is to describe a content negotiation process that uses scalable bitstreams in a generic way. In order to be able to express such an application, we felt the need for a better understanding of the data structures, in particular scalable bitstreams, on which this content negotiation process operates. Therefore, this thesis introduces a formal model we developed capable of describing the fundamental concepts of scalable bitstreams and their relations. Apart from the definition of the theoretical model itself, we demonstrate its correctness by applying it to a number of existing formats for scalable bitstreams. Furthermore, we attempt to formulate a content negotiation process as a constrained optimization problem, by means of the notations defined in the abstract model. In certain scenarios, the representation of a content negotiation process as a constrained optimization problem does not sufficiently reflect reality, especially when scalable bitstreams with multiple quality dimensions are involved. In such case, several versions of the same original bitstream can meet all constraints imposed by the system. Sometimes one version clearly offers a better quality towards the end user than another one, but in some cases, it is not possible to objectively compare two versions without additional information. In such a situation, a trade-off will have to be made between the different quality aspects. We use Pareto's theory of multi-criteria optimization for formally describing the characteristics of a content negotiation process for scalable bitstreams with multiple quality dimensions. This way, we can modify our definition of a content negotiation process into a multi-criteria optimization problem. One of the most important problems with multi-criteria optimization problems is that multiple candidate optimal solutions may exist. Additional information, e.g. user preferences, is needed if a single optimal solution has to be selected. Such multi-criteria optimization problems are not new. Unfortunately, existing solutions for selecting one optimal version are not suitable in a content negotiation scenario, because they expect detailed understanding of the problem from the decision maker, in our case the end user. In this thesis, we propose a scenario in which a so-called content negotiation agent would give some sample video sequences to the end user, asking him to select which sequence he liked the most. This information would be used for training the agent: a model would be built representing the preferences of the end user, and this model can be used later on for selecting one solution from a set of candidate optimal solutions. Based on a literature study, we propose two candidate algorithms in this thesis that can be used in such a content negotiation agent. It is possible to use these algorithms for constructing a model of the user's preferences by means of a number of examples, and to use this model when selecting an optimal version. The first algorithm considers the quality of a video sequence as a weighted sum of a number of independent quality aspects, and derives a system of linear inequalities from the example decisions. The second algorithm, called 1ARC, is actually a nearest-neighbor approach, where predictions are made based on the similarity with the example decisions entered by the user. This thesis analyzes the strengths and weaknesses of both algorithms from multiple points of view. The computational complexity of both algorithms is discussed, possible parameters that can influence the reliability of the algorithm, and the reliability itself. For measuring this kind of performance, we set up a test in which human subjects are asked to make a number of pairwise decisions between two versions of the same original video sequence. The reliability of the two algorithms we proposed is tested by selecting a part of these decisions for training a model, and by observing if this model is able to predict other decisions entered by the same user. We not only compare both algorithms, but we also observe the result of modifying several parameters on both algorithms. Ultimately, we conclude that the 1ARC algorithm has an acceptable performance, certainly if the training set is sufficiently large. The reliability is better than what would be theoretically achievable by any other algorithm that selects one optimal version from a set of candidate versions, but does not try to capture the user's preferences. Still, the results that we achieve are not as good as what we initially hoped. One possible cause may be the fact that the algorithms we proposed currently do not take sequence characteristics (e.g. the amount of motion) into account. Other improvements may be possible by means of a more accurate description of the quality aspects that we take into account, in particular the spatial resolution, the amount of distortion and the smoothness of a video sequence. Despite the limitations of the algorithms we proposed, in their performance as well as in their application area, we think that this thesis contains an initial and original contribution to the emerging objective of realizing Quality of Experience in multimedia applications

    {WAVA}: a New Web Service for Automatic Video Data Flow Adaptation in Heterogeneous Collaborative Environments

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    International audienceThe progressive needs for using video streaming for different applications in varied domains have created a new set of heterogeneous environments. In order to get the best performance of such environments, video streaming has to be adapted to the different parameters that characterize these environments, namely: bandwidth, CPU, GPU, screen resolution, etc. In this paper, we define a new web service, named Wava (Web service for Automatic Video Data Flows Adaptation). Wava allows multimedia platform to adjust the adaptation at two levels: the static level during initialization and the dynamic level according to the fluctuation of the environment
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