scholarly journals Influence of Resolution and Frame Rate on the Linear In-Stream Video Ad QoE

2014 ◽  
Vol 7 (1) ◽  
Author(s):  
Miloš Ljubojević ◽  
Vojkan Vasković ◽  
Zdenka Babić ◽  
Dušan Starčević
Keyword(s):  
Video Streaming ◽  
Quality Of Experience ◽  
Objective Assessment ◽  
Video Quality ◽  
Rate Change ◽  
Frame Rate ◽  
Strong Impact ◽  
Video Advertising ◽  
The Impact

Abstract: An increasing number of services and facilities that are of interest to users is based on video streaming. Technical characteristics of video have a strong impact on the quality of a video streaming service and its perception by users. The most important measure of quality, which focuses on the user, is the Quality of Experience (QoE). Given that video advertising is a typical video streaming application, it is necessary to analyze the effect of the change of video characteristics on the QoE. This paper examines the impact of resolution and frame rate change on the QoE level by using objective and subjective QoE metrics. It also looks at the possibility of mapping the objective QoE metrics into subjective ones, if the QoE in Internet video advertising is analyzed. It was demonstrated that the values obtained by the objective assessment of quality can be mapped to the results obtained by subjective assessment of quality when the quality of experience of linear in- stream video ads is analyzed. The results indicate that temporal aspects of video quality assessment, e.g. influence of resolution and frame rate change to the level of the QoE, can be achieved by implementation of objective methods. Therefore, quality of experience can be improved by the proper selection of video characteristics values.

scholarly journals Personalized Online Live Video Streaming Using Softmax-Based Multinomial Classification

2019 ◽  
Vol 9 (11) ◽  
pp. 2297
Author(s):  
Kyeongseon Kim ◽  
Dohyun Kwon ◽  
Joongheon Kim ◽  
Aziz Mohaisen
Keyword(s):  
Video Streaming ◽  
Waiting Time ◽  
Quality Of Experience ◽  
Video Quality ◽  
Live Video ◽  
Streaming Services ◽  
Online Streaming ◽  
Over The Top ◽  
User Content

As the demand for over-the-top and online streaming services exponentially increases, many techniques for Quality of Experience (QoE) provisioning have been studied. Users can take actions (e.g., skipping) while streaming a video. Therefore, we should consider the viewing pattern of users rather than the network condition or video quality. In this context, we propose a proactive content-loading algorithm for improving per-user personalized preferences using multinomial softmax classification. Based on experimental results, the proposed algorithm has a personalized per-user content waiting time that is significantly lower than that of competing algorithms.

scholarly journals The impact of quality of service parameters to the subjective and objective video quality assessment

2018 ◽  
Vol 15 (1) ◽  
pp. 97-114 ◽  
Author(s):  
Danilo Stanojevic ◽  
Boban Bondzulic ◽  
Boban Pavlovic ◽  
Vladimir Petrovic
Keyword(s):  
Quality Of Service ◽  
Subjective Experience ◽  
Objective Assessment ◽  
Video Quality ◽  
Destructive Effect ◽  
Objective Quality ◽  
Scatter Plots ◽  
Quality Of Service Parameters ◽  
The Impact

This paper deals with the delay, delay variation - jitter, packet loss rate and bandwidth as quality of service parameters, in the form of four types of video quality degradations. The impact of defined levels of degradation on subjective impressions (given as mean opinion scores) is analyzed. ReTRiEVED video dataset with publicly available subjective scores is used in the analysis. Three full-reference measures are used for objective assessment of video quality. The degree of consistency of subjective and objective quality scores is shown through scatter plots and quantitative measures (linear correlation coefficient and correlation of the ranks). Based on the interpolation functions, quality of service parameters are mapped to subjective experience. We show that jitter is a much more destructive effect than other degradation types.

scholarly journals Quality of Experience Measurement for Video Streaming Based On Adaptive Neural Fuzzy Inference System

2019 ◽  
pp. 1609-1617
Author(s):  
Rana Fareed Ghani ◽  
Amal Sufiuh Ajrash
Keyword(s):  
Video Streaming ◽  
Fuzzy Inference System ◽  
Quality Of Experience ◽  
Fuzzy Inference ◽  
Technological Development ◽  
Video Quality ◽  
Quality Measurement ◽  
Inference System ◽  
Neural Fuzzy

Technological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video streaming services is presented where the proposed metric does not require information on the original video. This work predicts QoE of videos by extracting features. Two types of features have been used, pixel-based features and network-based features. These features have been used to train an Adaptive Neural Fuzzy Inference System (ANFIS) to estimate the video QoE. 

scholarly journals A quality of experience-aware cross-layer architecture for optimizing video streaming services

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Video Streaming ◽  
Quality Of Experience ◽  
Video Quality ◽  
The Internet ◽  
Cross Layer ◽  
Video Traffic ◽  
Adaptive Architecture ◽  
Streaming Services ◽  
Simulation Results

The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture ).

scholarly journals Subjective Evaluation of User Quality of Experience for Omnidirectional Video Streaming

2020 ◽  
Vol 32 (3) ◽  
pp. 409-421
Author(s):  
Štefica Mrvelj ◽  
Marko Matulin ◽  
Sergo Martirosov
Keyword(s):  
Quality Of Experience ◽  
Subjective Evaluation ◽  
The Other ◽  
Frame Rate ◽  
Dynamic Scenes ◽  
Head Mounted Display ◽  
Subjective Testing ◽  
Perception Of Quality ◽  
The Impact

This paper reports on the results of subjective testing of user Quality of Experience (QoE) for omnidirectional video (ODV) streaming quality. The test was conducted among 20 test subjects who watched three ODVs using a Head Mounted Display (HMD) system. The length of the videos was between two and three minutes. The first video was used for training purposes and contained no quality degradations. The quality of the other two ODVs was degraded by manipulating the resolution or by introducing different frame drop patterns. While watching the pre-prepared videos the subjects indicated if they noticed the changes in the quality and then rated it. After watching each video, the subjects completed a separate questionnaire, which evaluated their level of enjoyment and discomfort with the video. The results showed that the degradation of both objective parameters (video resolution and frame rate) impacted the subjects’ perception of quality; however, the impact was somewhat alleviated in ODV which contained dynamic scenes and fast camera movements.

Quality of Experience (QOE) Aware Video Attributes Determination for Mobile Streaming Using Hybrid Profiling

2017 ◽  
Vol 8 (3) ◽  
pp. 597
Author(s):  
Muhamad Hanif Jofri ◽  
Mohd Farhan Md Fudzee ◽  
Mohd Norasri Ismail ◽  
SHAHREEN KASIM ◽  
Jemal Abawajy
Keyword(s):  
Energy Consumption ◽  
Quality Of Experience ◽  
Energy Use ◽  
Video Quality ◽  
Frame Rate ◽  
Online Video ◽  
Energy Aware ◽  
Hybrid Energy ◽  
Set Up

<p>Today, consumers use a smartphone device to display the media contents for work and entertainment purposes, as well as watching online video. Online video streaming is the main cause that consume smartphone’s energy quickly. To overcome this problem, smartphone’s energy management is crucial. Thus, a hybrid energy-aware profiler is proposed. Basically, a profiler will monitor and manage the energy consumption in the smartphone devices. The hybrid energy-aware profiler will set up a protocol preference of both the user and the device. Then, it will estimates the energy consumption in smartphone. However, saving energy alone can contribute to the Quality of Experience (QoE) neglection, thus the proposed solution takes into account the client QoE. Even though there are several existing energy-aware profilers that have been developed to manage energy use in smartphones however, most energy-aware profilers does not consider QoE at the same time. The proposed solution consider both, the performance of the hybrid energy-aware profiler is compared with the baseline energy models against a variation of content adaptation according to the pre-defined variables. Three types of variables were determined; resolution, frame rate and energy consumption in smartphone devices. In this area, QoE subjective methods based on MOS (Mean Opinion Score) are the most commonly used approaches for defining and quantifying real video quality. Nevertheless, although these approaches have been established to consistently quantify users’ amounts of approval, they do not adequately realize which are the criteria of video attribute that important. In this paper, we conducted an experiment with a certain devices to measures user’s QoE and energy usage of video attribute in smartphone devices. Our results demonstrate that the list of possible solution is a relevant and useful video attribute that satify the users.</p>

scholarly journals Mitigation of the Effects of Network Outage on Video QoE Using a Sender Buffer

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1209
Author(s):  
Tahir Nawaz Minhas ◽  
Markus Fiedler
Keyword(s):  
Quality Of Experience ◽  
Video Quality ◽  
Multimedia Applications ◽  
Mobile Internet ◽  
Live Streaming ◽  
End User ◽  
Analytical Relations ◽  
User Ratings ◽  
The Impact

With the growth of multimedia applications and the mobile Internet, quality sense and quality expectation of the end-user are rising rapidly. A small notable distortion in the multimedia applications may degrade the degree of delight of the user, who is very considerate of the video Quality of Experience (QoE). During live streaming, a network outage may result in video freezes and video jumps. To dampen the impact of a network outage on the video QoE, we propose the use of a well-sized sender buffer. We present the concept, derive key analytical relations, and perform a set of subjective tests. Based on those, we report a significant enhancement of user ratings due to the proposed sender buffer in the presence of network outages.

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