Evaluating Quality of Experience for Streaming Video in Real Time

“…Objective metrics have been developed to emulate the quality impression of the human visual system (HVS) to respond to the numerous tasks in industry and research that require automated methods to evaluate video quality [19]. The ability of performing MOS calculation in real time [20] can be very useful for ITS. Nevertheless in this paper we use EvalVid [19], a non real-time evaluation framework, for the video evaluation process.…”

Section: Evalvid the Evaluation Of Video Qoe And Qos Is Usually Perfmentioning

confidence: 99%

Multiple Interface Scheduling System for HeterogeneousWireless Vehicular Networks: Description and Evaluation

Román¹,

Ball²,

Ou³

2017

EAI Endorsed Transactions on Wireless Spectrum

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Reliable wireless communications between vehicles (V2V) and between vehicles and infrastructure (V2I) will play a key role in future transport networks. Where there is overlapping coverage of multiple Radio Access Technologies, with no cooperation between them, a vehicle can use the different technologies simultaneously. This paper proposes an uplink Multi Interface Scheduling System (MISS) located at an intermediate shim layer on the user side, to achieve efficient bandwidth aggregation, or lower end-to-end packet delay. MISS aims to find all the available networks that can meet multiple criteria based on user preference and required performance. Simulation results show that safety critical traffic can be prioritized where the resources are insufficient for all the services. Video delivery quality is also improved by prioritizing the most important frames. This algorithm is ideally suited to vehicular networks, where delivery of safety traffic and/or video is an essential requirement.

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“…However, the averaged value of the user ratings gathered in five-level ACR scale has a set of drawbacks such as the weakness in the definition of quality as summarized in [20,48]. In addition, it is influenced by the "forgiveness effect" [53]. As MOS might smooth out the low qualities, Hossfeld et al [15] introduced Standard Deviation of Opinion Scores (SOS) as it can better reveal the fluctuations of users' perceived quality.…”

Section: Inferring Qoe Based On Inter-picture Timementioning

confidence: 99%

VLQoE: Video QoE instrumentation on the smartphone

Ickin

Fiedler

Wac

et al. 2014

Multimed Tools Appl

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The usage of network-demanding applications is growing rapidly such as video streaming on mobile terminals. However, network and/or service providers might not guarantee the perceived quality for video streaming that demands high packet transmission rate. In order to satisfy the user expectations and to minimize user churn, it is important for network operators to infer the end-user perceived quality in video streaming. Today, the most reliable method to obtain end-user perceived quality is through subjective tests, and the preferred location is the user interface as it is the closest point of application to the enduser. The end-user perceived quality on video streaming is highly influenced by occasional freezes; technically the extraordinary time gaps between two consecutive pictures that are displayed to the user, i.e., high inter-picture time. In this paper, we present a QoE instrumentation for video streaming, VLQoE. We added functionality to the VLC player to record Multimed Tools Appl a set of metrics from the user interface, application-level, network-level, and from the available sensors of the device. To the best of our knowledge, VLQoE is the first tool of its kind that can be used in user experiments for video streaming. By using the tool, we present a two state model based on the inter-picture time, for the HTTP-and RTSP-based video streaming via 3.5G. Next, we studied the influence of inter-picture time on the user perceived quality through out a user study. We investigated the minimum user perceived inter-picture time, and the user response time.

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Evaluating Quality of Experience for Streaming Video in Real Time

Cited by 43 publications

References 12 publications

State-of-the-Practice in Evaluation of Quality of Experience in Real-Life Environments

State-of-the-Practice in Evaluation of Quality of Experience in Real-Life Environments

Multiple Interface Scheduling System for HeterogeneousWireless Vehicular Networks: Description and Evaluation

VLQoE: Video QoE instrumentation on the smartphone

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