1,984 research outputs found

    Q-AIMD: A Congestion Aware Video Quality Control Mechanism

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    Following the constant increase of the multimedia traffic, it seems necessary to allow transport protocols to be aware of the video quality of the transmitted flows rather than the throughput. This paper proposes a novel transport mechanism adapted to video flows. Our proposal, called Q-AIMD for video quality AIMD (Additive Increase Multiplicative Decrease), enables fairness in video quality while transmitting multiple video flows. Targeting video quality fairness allows improving the overall video quality for all transmitted flows, especially when the transmitted videos provide various types of content with different spatial resolutions. In addition, Q-AIMD mitigates the occurrence of network congestion events, and dissolves the congestion whenever it occurs by decreasing the video quality and hence the bitrate. Using different video quality metrics, Q-AIMD is evaluated with different video contents and spatial resolutions. Simulation results show that Q-AIMD allows an improved overall video quality among the multiple transmitted video flows compared to a throughput-based congestion control by decreasing significantly the quality discrepancy between them

    Towards one video encoder per individual : guided High Efficiency Video Coding

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    Cross layer techniques for flexible transport protocol using UDP-Lite over a satellite network

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    Traditional real-time multimedia and streaming services have utilised UDP over RTP. Wireless transmission, by its nature, may introduce a variable, sometimes high bit error ratio. Current transport layer protocols drop all corrupted packets, in contrast, protocols such as UDP-Lite allow error-resilient applications to be supported in the networking stack. This paper presents experimental quantitative performance metrics using H.264 and UDP Lite for the next generation transport of IP multimedia, and discusses the architectural implications for enhancing performance of a wireless and/or satellite environment

    A Bayesian Approach to Block Structure Inference in AV1-based Multi-rate Video Encoding

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    Due to differences in frame structure, existing multi-rate video encoding algorithms cannot be directly adapted to encoders utilizing special reference frames such as AV1 without introducing substantial rate-distortion loss. To tackle this problem, we propose a novel bayesian block structure inference model inspired by a modification to an HEVC-based algorithm. It estimates the posterior probabilistic distributions of block partitioning, and adapts early terminations in the RDO procedure accordingly. Experimental results show that the proposed method provides flexibility for controlling the tradeoff between speed and coding efficiency, and can achieve an average time saving of 36.1% (up to 50.6%) with negligible bitrate cost.Comment: published in IEEE Data Compression Conference, 201

    Exploiting and Evaluating Live 360° Low Latency Video Streaming Using CMAF

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    User Quality of Experience-aware Multimedia Streaming over Wireless Home Area Network

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    For multimedia streaming over wireless networks, there is a trade-off between the capacity of the wireless links and the end-user perceived-quality, which can be affected by the compression scheme used, content characteristics and adaptation algorithm (if any). In this paper, this trade-off is investigated for streaming various motion content multimedia over an IEEE 802.11b-based Wireless-Home Area Network using the Quality-Oriented Adaptation Scheme (QOAS). QOAS performance is compared to that of a non-adaptive scheme when using MPEG-2 and MPEG-4 encoding in terms of average end-user perceived quality, number of streaming sessions concurrently supported, loss rate, delay, jitter and total throughput. Simulation results show that by using QOAS and MPEG-4 encoded streams a much higher number of concurrent streams are supported at an average quality above “good” level on the ITU-T five-point quality scale in comparison with other situations. In this case all the other streaming performance parameters were also significantly better

    Reducing the complexity of a multiview H.264/AVC and HEVC hybrid architecture

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    With the advent of 3D displays, an efficient encoder is required to compress the video information needed by them. Moreover, for gradual market acceptance of this new technology, it is advisable to offer backward compatibility with existing devices. Thus, a multiview H.264/Advance Video Coding (AVC) and High Efficiency Video Coding (HEVC) hybrid architecture was proposed in the standardization process of HEVC. However, it requires long encoding times due to the use of HEVC. With the aim of tackling this problem, this paper presents an algorithm that reduces the complexity of this hybrid architecture by reducing the encoding complexity of the HEVC views. By using Na < ve-Bayes classifiers, the proposed technique exploits the information gathered in the encoding of the H.264/AVC view to make decisions on the splitting of coding units in HEVC side views. Given the novelty of the proposal, the only similar work found in the literature is an unoptimized version of the algorithm presented here. Experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity
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