Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

Quick estimation of end to end PQoS of image

本文介绍了一种新型的利用图像活动性(IAM)快速估计水下图像端到端体验质量的方法。首先引入结构相似度(SSIM)作为图像感知服务质量(PQo S)参数评价图像质量,将图像初始活动性(IAM)作为区分图像内容的本征参数;随后基于质量向量(QV)的概念,分别分析了非压缩图像的结构相似度,图像初实活动性与无条件丢失概率(SSIM-IAM.-ulp)之间的联合特性,以及压缩图像的结构相似性,压缩率与无条件丢失概率(SSIM-IAM.-ulp)之间的联合特性。最后,在上述联合特性的基础上提出了劣化图像SSIM的预测算法。测试实验证明,该类算法有较高的预测准确率,预测误差最低可达0.8%。This paper introduces a novel method for quick estimating the end to end Perceived Quality of Service( PQo S) of underwater image based on image activity measure( IAM). Structure Similarity( SSIM) is first introduced as the evaluation standard of image PQo S parameter to evaluate the quality of image,while the IAM of original image is utilized as an intrinsic parameter to discriminate the image contents. Then,based on the concept of quality vector( QV),the SSIM-ulp-IAM0 features for non-compressed picture are analyzed,and the SSIM-CR-ulp features for compressed picture are analyzed as well. On this basis,the prediction algorithm based on SSIM for the degraded image is proposed. Test experiment result shows that this kind of prediction algorithm has high accuracy rate,and the lowest prediction error reaches to 0. 8%.国家自然科学基金面上(61571377;61471308)项目资

Adapted IPTV Service within novel IMS Architecture

International audienc

Packet-Layer Quality Assessment for Networked Video

To realize real-time and non-intrusive quality monitoring for networked video, a content-adaptive packet-layer model for quality assessment is proposed. Considering the fact that the coding distortion of a video is dependent not only on the bit-rate but also on the motion characteristic of the video content, temporal complexity is evaluated and incorporated in quality assessment in the proposed model. Since very limited information is available for a packet-layer model, an adaptive method for frame type detection is first applied. Then the temporal complexity which reflects the motion characteristic of the video content is estimated using the ratio of the bit-rate for coding I frames and P frames. The estimated temporal complexity is incorporated in the proposed model, making it adaptive to different video content. Experimental results show that the proposed model achieves an advanced performance in comparison with the ITU-T G.1070 model

A reduced reference video quality assessment method for provision as a service over SDN/NFV-enabled networks

139 p.The proliferation of multimedia applications and services has generarted a noteworthy upsurge in network traffic regarding video content and has created the need for trustworthy service quality assessment methods. Currently, predominent position among the technological trends in telecommunication networkds are Network Function Virtualization (NFV), Software Defined Networking (SDN) and 5G mobile networks equipped with small cells. Additionally Video Quality Assessment (VQA) methods are a very useful tool for both content providers and network operators, to understand of how users perceive quality and this study the feasibility of potential services and adapt the network available resources to satisfy the user requirements

A reduced reference video quality assessment method for provision as a service over SDN/NFV-enabled networks

139 p.The proliferation of multimedia applications and services has generarted a noteworthy upsurge in network traffic regarding video content and has created the need for trustworthy service quality assessment methods. Currently, predominent position among the technological trends in telecommunication networkds are Network Function Virtualization (NFV), Software Defined Networking (SDN) and 5G mobile networks equipped with small cells. Additionally Video Quality Assessment (VQA) methods are a very useful tool for both content providers and network operators, to understand of how users perceive quality and this study the feasibility of potential services and adapt the network available resources to satisfy the user requirements

Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission

The aim of this thesis is to present a new shaped Variable Bit Rate (VBR) for video transmission, which plays a crucial role in delivering video traffic over the Internet. This is due to the surge of video media applications over the Internet and the video typically has the characteristic of a highly bursty traffic, which leads to the Internet bandwidth fluctuation. This new shaped algorithm, referred to as Slight Delay - Shaped Variable Bit Rate (SD-SVBR), is aimed at controlling the video rate for video application transmission. It is designed based on the Shaped VBR (SVBR) algorithm and was implemented in the Network Simulator 2 (ns-2). SVBR algorithm is devised for real-time video applications and it has several limitations and weaknesses due to its embedded estimation or prediction processes. SVBR faces several problems, such as the occurrence of unwanted sharp decrease in data rate, buffer overflow, the existence of a low data rate, and the generation of a cyclical negative fluctuation. The new algorithm is capable of producing a high data rate and at the same time a better quantization parameter (QP) stability video sequence. In addition, the data rate is shaped efficiently to prevent unwanted sharp increment or decrement, and to avoid buffer overflow. To achieve the aim, SD-SVBR has three strategies, which are processing the next Group of Picture (GoP) video sequence and obtaining the QP-to-data rate list, dimensioning the data rate to a higher utilization of the leaky-bucket, and implementing a QP smoothing method by carefully measuring the effects of following the previous QP value. However, this algorithm has to be combined with a network feedback algorithm to produce a better overall video rate control. A combination of several video clips, which consisted of a varied video rate, has been used for the purpose of evaluating SD-SVBR performance. The results showed that SD-SVBR gains an impressive overall Peak Signal-to-Noise Ratio (PSNR) value. In addition, in almost all cases, it gains a high video rate but without buffer overflow, utilizes the buffer well, and interestingly, it is still able to obtain smoother QP fluctuation

Video Quality Assessment in Underwater Acoustic Networks

Fecha de Lectura de Tesis Doctoral: 23 de mayo de 2018.Las imágenes subacuáticas reciben una atención cada vez mayor por parte de la comunidad científica dado que las fotografías y los vídeos son herramientas de gran valor en el estudio del entorno oceánico que cubre el 90% de la biosfera de nuestro planeta. Sin embargo, las Redes de Sensores Submarinas deben enfrentarse al canal hostil que el agua de mar constituye. Las comunicaciones de medio rango son sólo posibles con modems acústicos de capacidades muy limitadas con tasas binarias de pico de unas decenas de kbps. En transmisión de vídeo, estas reducidas tasas binarias fuerzan una compresión elevada que produce niveles de distorsión mucho mayores que en otros entornos. Además, los usuarios de vídeo submarino son oceanógrafos u otros especialistas con una percepción de la calidad diferente a la de un grupo genérico de usuarios. Las peculiaridades descritas exigen un estudio dedicado de la evaluación de calidad de vídeo para redes submarinas. Esta tesis doctoral aborda el problema de la evaluación de calidad de vídeo y presenta contribuciones en las dos áreas principales de esta disciplina: evaluación subjetiva y evaluación objetiva. La referencia para la percepción de calidad en cualquier servicio es la opinión de los usuarios y, por tanto, un análisis de la calidad subjetiva es el primer paso en este trabajo. Se presentan el diseño experimental y los resultados de un test de acuerdo a métodos psicométricos estándares. Los participantes del test fueron científicos del océano y las secuencias de vídeo utilizadas fueron grabadas en campañas de exploración y procesadas para simular las condiciones de las comunicaciones submarinas. Los resultados experimentales muestran como los vídeos son útiles para tareas científicas incluso en condiciones de muy baja tasa binaria. Los métodos de evaluación de la calidad objetiva son algoritmos diseñados para calcular puntuaciones de calidad

Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

Video Content-Based QoE Prediction for HEVC Encoded Videos Delivered over IP Networks

The recently released High Efficiency Video Coding (HEVC) standard, which halves the transmission bandwidth requirement of encoded video for almost the same quality when compared to H.264/AVC, and the availability of increased network bandwidth (e.g. from 2 Mbps for 3G networks to almost 100 Mbps for 4G/LTE) have led to the proliferation of video streaming services. Based on these major innovations, the prevalence and diversity of video application are set to increase over the coming years. However, the popularity and success of current and future video applications will depend on the perceived quality of experience (QoE) of end users. How to measure or predict the QoE of delivered services becomes an important and inevitable task for both service and network providers. Video quality can be measured either subjectively or objectively. Subjective quality measurement is the most reliable method of determining the quality of multimedia applications because of its direct link to users’ experience. However, this approach is time consuming and expensive and hence the need for an objective method that can produce results that are comparable with those of subjective testing. In general, video quality is impacted by impairments caused by the encoder and the transmission network. However, videos encoded and transmitted over an error-prone network have different quality measurements even under the same encoder setting and network quality of service (NQoS). This indicates that, in addition to encoder settings and network impairment, there may be other key parameters that impact video quality. In this project, it is hypothesised that video content type is one of the key parameters that may impact the quality of streamed videos. Based on this assertion, parameters related to video content type are extracted and used to develop a single metric that quantifies the content type of different video sequences. The proposed content type metric is then used together with encoding parameter settings and NQoS to develop content-based video quality models that estimate the quality of different video sequences delivered over IP-based network. This project led to the following main contributions: (1) A new metric for quantifying video content type based on the spatiotemporal features extracted from the encoded bitstream. (2) The development of novel subjective test approach for video streaming services. (3) New content-based video quality prediction models for predicting the QoE of video sequences delivered over IP-based networks. The models have been evaluated using subjective and objective methods