27 research outputs found

    Content-Aware Scalability-Type Selection for Rate Adaptation of Scalable Video

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    Scalable video coders provide different scaling options, such as temporal, spatial, and SNR scalabilities, where rate reduction by discarding enhancement layers of different scalability-type results in different kinds and/or levels of visual distortion depend on the content and bitrate. This dependency between scalability type, video content, and bitrate is not well investigated in the literature. To this effect, we first propose an objective function that quantifies flatness, blockiness, blurriness, and temporal jerkiness artifacts caused by rate reduction by spatial size, frame rate, and quantization parameter scaling. Next, the weights of this objective function are determined for different content (shot) types and different bitrates using a training procedure with subjective evaluation. Finally, a method is proposed for choosing the best scaling type for each temporal segment that results in minimum visual distortion according to this objective function given the content type of temporal segments. Two subjective tests have been performed to validate the proposed procedure for content-aware selection of the best scalability type on soccer videos. Soccer videos scaled from 600 kbps to 100 kbps by the proposed content-aware selection of scalability type have been found visually superior to those that are scaled using a single scalability option over the whole sequence

    ON OPTIMAL ROYALTY COSTS FOR VIDEO COMPRESSION

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    Modern video compression includes a mature set of codecs, tools, and techniques that correspond to a variety of coding efficiencies and royalty costs in video delivery. In early work we showed that there can be significant benefits to employing a royalty-aware encoder that jointly optimizes rate, distortion, and royalty cost by choosing among several codecs having different royalty costs [1]. In this paper we assume the existence of such an encoder and concentrate on how royalty costs should be assigned to benefit a system of users, video service providers, and tool/codec owners. Our work operates on the intersection of rate-distortion principles with basic concepts from economics and tries to address issues that are rapidly becoming very relevant in media delivery. Using a simple model that captures user preferences of video quality levels (given costs associated with these levels), we formulate the assignment of royalty costs as an optimization problem and solve it for optimal costs for several scenarios. The main trade-offs that govern our results are the cost of bandwidth and previously unachievable quality levels (if any) that a state-of-the-art codec gives access to. We show that content-based cost assignment not only increases user utilization but also the royalty earnings for tool owners compared to content-unaware pricing policies. Index Terms — Image coding, video coding, royalty cost, pricing, H.264/AVC, video standards

    Royalty Cost Based Optimization for Video Compression

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    A video compression standard incorporates many tools and technologies which must be licensed by systems that deploy the standard. The licensing determines the royalty costs that must be paid to the holders of intellectual property on the respective tools. With current abundance of well understood and effective video compression tools, one can imagine the formation of cross cutting tool libraries with tools drawn from different video compression standards. This allows dynamic selection from a large pool of tools, having potentially overlapping functionality, when encoding individual video sequences. In this paper we examine the royalty cost aspect of the scenario where video is encoded using a library of royalty bearing tools by considering encoding that jointly optimizes rate, distortion, and royalty cost. We provide a system that optimizes video delivery under various licensing conditions imposed on tool intellectual property. We present an example of royalty based encoding (using assumed royalty costs) to show the merit of the proposed framework. 1

    Media streaming with network diversity

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    Today's packet networks including the Internet offer an intrinsic diversity for media distribution in terms of available network paths and servers or information sources. Novel communication infrastructures such as ad hoc or wireless mesh networks use network diversity to extend their reach at low cost. Diversity can bring interesting benefits in supporting resource greedy applications such as media streaming services, by aggregation of bandwidth and computing resources. Typically, overlay network architectures compensate for lack of quality-of-service guarantees in the network by introducing redundancy in the media delivery system through network diversity. They can support efficient multimedia services when routing, coding, and scheduling algorithms are able to adapt to both the media information and the dynamic network status. This paper presents an overview of the distributed streaming solutions that profit from network diversity in order to improve the quality of multimedia applications. We discuss the coding techniques used for adaptive and flexible media streaming with network diversity. We describe the problem of media streaming with path diversity and focus on routing, path computation, and packet scheduling problems in multipath networks. Then, the advantages of server or source peer diversity in collaborative streaming solutions are discussed. Lastly, we present an overview of wireless mesh networks and focus on the typical constraints imposed by these novel communication models on media streaming with network diversit
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