71 research outputs found

    3D video coding and transmission

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    The capture, transmission, and display of 3D content has gained a lot of attention in the last few years. 3D multimedia content is no longer con fined to cinema theatres but is being transmitted using stereoscopic video over satellite, shared on Blu-RayTMdisks, or sent over Internet technologies. Stereoscopic displays are needed at the receiving end and the viewer needs to wear special glasses to present the two versions of the video to the human vision system that then generates the 3D illusion. To be more e ffective and improve the immersive experience, more views are acquired from a larger number of cameras and presented on di fferent displays, such as autostereoscopic and light field displays. These multiple views, combined with depth data, also allow enhanced user experiences and new forms of interaction with the 3D content from virtual viewpoints. This type of audiovisual information is represented by a huge amount of data that needs to be compressed and transmitted over bandwidth-limited channels. Part of the COST Action IC1105 \3D Content Creation, Coding and Transmission over Future Media Networks" (3DConTourNet) focuses on this research challenge.peer-reviewe

    Optical network technologies for future digital cinema

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    Digital technology has transformed the information flow and support infrastructure for numerous application domains, such as cellular communications. Cinematography, traditionally, a film based medium, has embraced digital technology leading to innovative transformations in its work flow. Digital cinema supports transmission of high resolution content enabled by the latest advancements in optical communications and video compression. In this paper we provide a survey of the optical network technologies for supporting this bandwidth intensive traffic class. We also highlight the significance and benefits of the state of the art in optical technologies that support the digital cinema work flow

    Studying Rate Control Methods for UHDTV Delivery Using HEVC

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    Since the early video coding standardisation efforts, rate control has been considered essential for almost any application, and has therefore been extensively studied. With the advent of improved video coding standards, such as the current stateof-the-art High Efficiency Video Coding (HEVC) standard, and the introduction of advanced flexible coding tools, previous Rate-Distortion (RD) models used for rate control have become obsolete. To address this issue, some rate control methods have been recently proposed specifically for HEVC which introduce many useful features, such as a robust correspondence between the rate and Lagrange multiplier . However, when applying these rate control methods on sequences in the new Ultra High Definition Television (UHDTV) format, degraded coding performance was observed. In this paper, an analysis of the state-of-the-art HEVC rate control method was performed and two directions for its improvement were evaluated. These improvements target frame-level bit-allocation and model parameter initialisation. When compared to the rate control method implemented in the HEVC reference software, these improvements result in reduced BDrate losses of 3:1% and 2:1%, versus the 8:8% provided by the reference algorithm. Moreover, the proposed improvements improve the accuracy in hitting the target bit-rate./p

    Two-Pass Rate Control for Improved Quality of Experience in UHDTV Delivery

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    End to end Multi-Objective Optimisation of H.264 and HEVC Codecs

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    All multimedia devices now incorporate video CODECs that comply with international video coding standards such as H.264 / MPEG4-AVC and the new High Efficiency Video Coding Standard (HEVC) otherwise known as H.265. Although the standard CODECs have been designed to include algorithms with optimal efficiency, large number of coding parameters can be used to fine tune their operation, within known constraints of for e.g., available computational power, bandwidth, consumer QoS requirements, etc. With large number of such parameters involved, determining which parameters will play a significant role in providing optimal quality of service within given constraints is a further challenge that needs to be met. Further how to select the values of the significant parameters so that the CODEC performs optimally under the given constraints is a further important question to be answered. This thesis proposes a framework that uses machine learning algorithms to model the performance of a video CODEC based on the significant coding parameters. Means of modelling both the Encoder and Decoder performance is proposed. We define objective functions that can be used to model the performance related properties of a CODEC, i.e., video quality, bit-rate and CPU time. We show that these objective functions can be practically utilised in video Encoder/Decoder designs, in particular in their performance optimisation within given operational and practical constraints. A Multi-objective Optimisation framework based on Genetic Algorithms is thus proposed to optimise the performance of a video codec. The framework is designed to jointly minimize the CPU Time, Bit-rate and to maximize the quality of the compressed video stream. The thesis presents the use of this framework in the performance modelling and multi-objective optimisation of the most widely used video coding standard in practice at present, H.264 and the latest video coding standard, H.265/HEVC. When a communication network is used to transmit video, performance related parameters of the communication channel will impact the end-to-end performance of the video CODEC. Network delays and packet loss will impact the quality of the video that is received at the decoder via the communication channel, i.e., even if a video CODEC is optimally configured network conditions will make the experience sub-optimal. Given the above the thesis proposes a design, integration and testing of a novel approach to simulating a wired network and the use of UDP protocol for the transmission of video data. This network is subsequently used to simulate the impact of packet loss and network delays on optimally coded video based on the framework previously proposed for the modelling and optimisation of video CODECs. The quality of received video under different levels of packet loss and network delay is simulated, concluding the impact on transmitted video based on their content and features
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