Subjective Assessment of Region of Interest-Aware Adaptive Multimedia Streaming Quality

Ciubotaru, Bogdan; Ghinea, Gheorghiţă; Muntean, Gabriel‐Miro

doi:10.1109/tbc.2013.2290238

Cited by 27 publications

(15 citation statements)

References 48 publications

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“…Some studies have already had some attempts in this regard. As an example of studies which consider the content for designing the adaptation scheme is [36]. According to this adaptation scheme, regions within each frame of the streamed content are adapted differently according to the user interest on them.…”

Section: Discussionmentioning

confidence: 99%

Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies

Tavakoli

Egger

Seufert

et al. 2016

IEEE J. Select. Areas Commun.

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Abstract-Today's packet-switched networks are subject to bandwidth fluctuations that cause for degradation of user experience of multimedia services. In order to cope with this problem, HTTP Adaptive Streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services such as Netflix and Youtube. HAS enables service providers to improve users' Quality of Experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting timevarying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite of various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters including chunk length, switching amplitude, switching frequency and temporal recency are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. Statistical analysis of the combined dataset reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g. interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.

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Section: Discussionmentioning

confidence: 99%

Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies

Tavakoli

Egger

Seufert

et al. 2016

IEEE J. Select. Areas Commun.

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“…The saccade is a rapid eye movement that allows jumping from one location to another. The purpose of these movements is to bring the images of particular areas of the visual field, named region of interest, to fall onto the fovea in order to improve our selective attention [45]- [47]. Video is one of the most common ways to capture visual information.…”

Section: Relation Between the Dash Standard And The Ifs On Qualitymentioning

confidence: 99%

Video Quality Metric for Streaming Service Using DASH Standard

Rodríguez

Rosa

Alfaia

et al. 2016

IEEE Trans. on Broadcast.

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Currently, dynamic adaptive streaming over HTTP (DASH) standard is used to change the video resolution according to the network capacity of the end user's. However, if the video resolution changes frequently, the attention of the users can be affected decreasing their quality-of-experience (QoE). In this context, this paper proposes a no-reference video quality metric that takes three impairment factors into account, initial buffering delay, temporal interruptions or pauses, and video resolution changes during a video transmission. Also, the temporal locations of pauses and resolution changes are considered. In order to perform this task, extensive subjective tests were conducted. Experimental results show that the evaluators' QoE is highly correlated with the frequency of pauses, video resolution changes and initial delay. Based on these results a video streaming quality metric for DASH services (VsQM DASH ) is formulated and implemented on PC and mobile hand-held devices. Finally, the performance of VsQM DASH is validated with additional subjective tests reaching a person correlation coefficient of 0.99. Furthermore, experimental results demonstrated that the proposed metric has low complexity because it is based on application level parameters and its energy consumption is negligible in relation to the energy consumed by the video player; therefore, can be easily implemented in consumer electronic devices.

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“…By analyzing moving objects and luminance variation in specific regions, adaptive video streaming using the video quality of each ROI can be employed to improve the QoE [92].…”

Section: Future Directions and Challengesmentioning

confidence: 99%