Tube streaming: Modelling collaborative media streaming in urban railway networks

We propose a quality assessment framework for crowdsourced media streaming in urban railway networks. We assume that commuters either tune in to some TV/radio channel, or submit requests for content they desire to watch or listen to, which eventually forms a playlist of videos/podcasts/tunes. Given that connectivity is challenged by the movement of trains and the disconnection that this movement causes, users collabo-ratively download (through cellular and WiFi connections) and share content, in order to maintain undisrupted playback. We model collaborative media streaming for the case of the London Underground train network. The proposed quality assessment framework comprises a utility function which characterises the Quality of Experience (QoE) that users (subjectively) perceive and takes into account all the necessary parameters that affect smooth playback. The framework can be used to assess the media streaming quality in any railway network, after adjusting the related parameters. To the best of our knowledge, this is the first study to quantify the perceptual quality of collaborative media streaming in (underground) railway networks from a modelling perspective, as opposed to a systems perspective. Based on real commuter traces from the London Underground network, we evaluate whether audio and video can be streamed to commuters with acceptable QoE. Our results show that even with very high-speed Internet connection, users still experience disruptions, but a carefully designed collaborative mechanism can result in high levels of perceived QoE even in such disruptive scenarios

Providing 3D video services: the challenge from 2D to 3DTV quality of experience

Recently, three-dimensional (3D) video has decisively burst onto the entertainment industry scene, and has arrived in households even before the standardization process has been completed. 3D television (3DTV) adoption and deployment can be seen as a major leap in television history, similar to previous transitions from black and white (B&W) to color, from analog to digital television (TV), and from standard definition to high definition. In this paper, we analyze current 3D video technology trends in order to define a taxonomy of the availability and possible introduction of 3D-based services. We also propose an audiovisual network services architecture which provides a smooth transition from two-dimensional (2D) to 3DTV in an Internet Protocol (IP)-based scenario. Based on subjective assessment tests, we also analyze those factors which will influence the quality of experience in those 3D video services, focusing on effects of both coding and transmission errors. In addition, examples of the application of the architecture and results of assessment tests are provided

Democratic Replay: Enhancing TV Election Debates with Interactive Visualisations

This paper presents an online platform for enhancing televised election debates with interactive visualisations. Election debates are one of the highlights of election campaigns worldwide. They are also often criticised as appearing scripted, rehearsed, detached from much of the electorate, and at times too complex. Democratic Replay enhances videos of election debates with a collection of interactive tools aimed at providing a replay experience centred around citizens' needs. We present the system requirements, design and implementation, and report on an evaluation based on the ITV Leaders' Debate from the 2015 UK General Election campaign

Assessing quality of experience of IPTV and video on demand services in real-life environments

The ever growing bandwidth in access networks, in combination with IPTV and video on demand (VoD) offerings, opens up unlimited possibilities to the users. The operators can no longer compete solely on the number of channels or content and increasingly make high definition channels and quality of experience (QoE) a service differentiator. Currently, the most reliable way of assessing and measuring QoE is conducting subjective experiments, where human observers evaluate a series of short video sequences, using one of the international standardized subjective quality assessment methodologies. Unfortunately, since these subjective experiments need to be conducted in controlled environments and pose limitations on the sequences and overall experiment duration they cannot be used for real-life QoE assessment of IPTV and VoD services. In this article, we propose a novel subjective quality assessment methodology based on full-length movies. Our methodology enables audiovisual quality assessment in the same environments and under the same conditions users typically watch television. Using our new methodology we conducted subjective experiments and compared the outcome with the results from a subjective test conducted using a standardized method. Our findings indicate significant differences in terms of impairment visibility and tolerance and highlight the importance of real-life QoE assessment

Streaming Video QoE Modeling and Prediction: A Long Short-Term Memory Approach

HTTP based adaptive video streaming has become a popular choice of streaming due to the reliable transmission and the flexibility offered to adapt to varying network conditions. However, due to rate adaptation in adaptive streaming, the quality of the videos at the client keeps varying with time depending on the end-to-end network conditions. Further, varying network conditions can lead to the video client running out of playback content resulting in rebuffering events. These factors affect the user satisfaction and cause degradation of the user quality of experience (QoE). It is important to quantify the perceptual QoE of the streaming video users and monitor the same in a continuous manner so that the QoE degradation can be minimized. However, the continuous evaluation of QoE is challenging as it is determined by complex dynamic interactions among the QoE influencing factors. Towards this end, we present LSTM-QoE, a recurrent neural network based QoE prediction model using a Long Short-Term Memory (LSTM) network. The LSTM-QoE is a network of cascaded LSTM blocks to capture the nonlinearities and the complex temporal dependencies involved in the time varying QoE. Based on an evaluation over several publicly available continuous QoE databases, we demonstrate that the LSTM-QoE has the capability to model the QoE dynamics effectively. We compare the proposed model with the state-of-the-art QoE prediction models and show that it provides superior performance across these databases. Further, we discuss the state space perspective for the LSTM-QoE and show the efficacy of the state space modeling approaches for QoE prediction

The Learning Effectiveness of Cross-Discipline Collaboration within Media Production BA Projects

This paper considers the learning potential released by teaching to groups across different disciplines within media production. A single six week unit was delivered to eighteen groups of students, each group comprising a mix from BA Television Production, BA Interactive Media Production and BA Scriptwriting for Film and Television, all at level C. Each group of approximately nine students was required to create a DVD programme with associated website on the topic of ‘crime prevention’. The paper considers the logistics of organising and delivering the programme and the ways in which staff and students related to the cross-discipline nature of the unit. It also considers the approaches taken to assess the students and their project work. The investigation involved a mixture of questionnaires and interviews conducted after completion of the unit

Sedentary behaviour and diet across the lifespan: an updated systematic review.

Sedentary behaviour and its association with dietary intake in young people and adults are important topics and were systematically reviewed in 2011. There is a need to update this evidence given the changing nature of sedentary behaviour and continued interest in this field. This review aims to assist researchers in better interpreting the diversity of findings concerning sedentary behaviour and weight status