Video streaming

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Comparing objective visual quality impairment detection in 2D and 3D video sequences

The skill level of teleoperator plays a key role in the telerobotic operation. However, plenty of experiments are required to evaluate the skill level in a conventional assessment. In this paper, a novel brain-based method of skill assessment is introduced, and the relationship between the teleoperator's brain states and skill level is first investigated based on a kernel canonical correlation analysis (KCCA) method. The skill of teleoperator (SoT) is defined by a statistic method using the cumulative probability function (CDF). Five indicators are extracted from the electroencephalo-graph (EEG) of the teleoperator to represent the brain states during the telerobotic operation. By using the KCCA algorithm in modeling the relationship between the SoT and the brain states, the correlation has been proved. During the telerobotic operation, the skill level of teleoperator can be well predicted through the brain states. © 2013 IEEE.Link_to_subscribed_fulltex

3D multiple description coding for error resilience over wireless networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Mobile communications has gained a growing interest from both customers and service providers alike in the last 1-2 decades. Visual information is used in many application domains such as remote health care, video –on demand, broadcasting, video surveillance etc. In order to enhance the visual effects of digital video content, the depth perception needs to be provided with the actual visual content. 3D video has earned a significant interest from the research community in recent years, due to the tremendous impact it leaves on viewers and its enhancement of the user’s quality of experience (QoE). In the near future, 3D video is likely to be used in most video applications, as it offers a greater sense of immersion and perceptual experience. When 3D video is compressed and transmitted over error prone channels, the associated packet loss leads to visual quality degradation. When a picture is lost or corrupted so severely that the concealment result is not acceptable, the receiver typically pauses video playback and waits for the next INTRA picture to resume decoding. Error propagation caused by employing predictive coding may degrade the video quality severely. There are several ways used to mitigate the effects of such transmission errors. One widely used technique in International Video Coding Standards is error resilience. The motivation behind this research work is that, existing schemes for 2D colour video compression such as MPEG, JPEG and H.263 cannot be applied to 3D video content. 3D video signals contain depth as well as colour information and are bandwidth demanding, as they require the transmission of multiple high-bandwidth 3D video streams. On the other hand, the capacity of wireless channels is limited and wireless links are prone to various types of errors caused by noise, interference, fading, handoff, error burst and network congestion. Given the maximum bit rate budget to represent the 3D scene, optimal bit-rate allocation between texture and depth information rendering distortion/losses should be minimised. To mitigate the effect of these errors on the perceptual 3D video quality, error resilience video coding needs to be investigated further to offer better quality of experience (QoE) to end users. This research work aims at enhancing the error resilience capability of compressed 3D video, when transmitted over mobile channels, using Multiple Description Coding (MDC) in order to improve better user’s quality of experience (QoE). Furthermore, this thesis examines the sensitivity of the human visual system (HVS) when employed to view 3D video scenes. The approach used in this study is to use subjective testing in order to rate people’s perception of 3D video under error free and error prone conditions through the use of a carefully designed bespoke questionnaire.Petroleum Technology Development Fund (PTDF

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

VIQID: a no-reference bit stream-based visual quality impairment detector

In order to ensure adequate quality towards the end users at all time, video service providers are getting more interested in monitoring their video streams. Objective video quality metrics provide a means of measuring (audio)visual quality in an automated manner. Unfortunately, most of the current existing metrics cannot be used for real-time monitoring due to their dependencies on the original video sequence. In this paper we present a new objective video quality metric which classifies packet loss as visible or invisible based on information extracted solely from the captured encoded H.264/AVC video bit stream. Our results show that the visibility of packet loss can be predicted with a high accuracy, without the need for deep packet inspection. This enables service providers to monitor quality in real-time