Bandwidth Reduction of Omnidirectional Viewport-Dependent Video Streaming via Subjective Quality Assessment

Curcio, Igor D. D.; Toukomaa, Henri; Naik, Deepa

doi:10.1145/3132361.3132364

Cited by 29 publications

(6 citation statements)

References 9 publications

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“…When evaluating compression schemes, Differential Mean Opinion Score (DMOS) is often used as a DCR metric, evaluating the difference between the quality of the compressed content and the original's: this is a fundamental step of the evaluation of new coding schemes, for both standard and omnidirectional content [99]. Omnidirectional video content is even more challenging, as static image quality is not the only component that influences QoE, and even subjective studies need to consider FoV changes and how the different encoding of foreground and background affects the experience [100]. A testing methodology that considers the dynamic aspect of QoE, accounting for delays between user motion and the high-quality rendering of the video in the new direction, is presented in [101].…”

Section: Measuring Qoe: Subjective Methodsmentioning

confidence: 99%

“…The authors of [114] also released their dataset, with 21 participants watching 75 impaired video sequences with different resolution and compression levels. There are other small-scale datasets associated to other measurement studies [100,115], while two more large dataset, with 13 subject watching 150 videos and 23 subjects watching 384, were presented in [116] and [117], respectively. To the best of our knowledge, the largest available dataset was presented in [118], and is divided in 5 scenarios with an approximately uniform division of samples.…”

Section: Measuring Qoe: Subjective Methodsmentioning

confidence: 99%

“…In [269], the popularity-based prediction is used to derive an adaptive projection with an irregular shape. The trade-off between changing the compression of the tiles at the same resolution and lowering the resolution to increase the bandwidth efficiency has also been explored [100], and the results show that the viewport-based approach has a higher QoE with the same compression.…”

Section: Viewport-dependent Streamingmentioning

confidence: 99%

See 2 more Smart Citations

A Survey on 360-Degree Video: Coding, Quality of Experience and Streaming

Chiariotti¹

2021

Preprint

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The commercialization of Virtual Reality (VR) headsets has made immersive and 360 • video streaming the subject of intense interest in the industry and research communities. While the basic principles of video streaming are the same, immersive video presents a set of specific challenges that need to be addressed. In this survey, we present the latest developments in the relevant literature on four of the most important ones: (i) omnidirectional video coding and compression, (ii) subjective and objective Quality of Experience (QoE) and the factors that can affect it, (iii) saliency measurement and Field of View (FoV) prediction, and (iv) the adaptive streaming of immersive 360 • videos.The final objective of the survey is to provide an overview of the research on all the elements of an immersive video streaming system, giving the reader an understanding of their interplay and performance.

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Section: Measuring Qoe: Subjective Methodsmentioning

confidence: 99%

Section: Measuring Qoe: Subjective Methodsmentioning

confidence: 99%

Section: Viewport-dependent Streamingmentioning

confidence: 99%

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A Survey on 360-Degree Video: Coding, Quality of Experience and Streaming

Chiariotti¹

2021

Preprint

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“…It is observed that the equal-area mapping yields around 8.3% bitrate savings relative to the commonly used equirectangular mapping. Ghaznavi-Youvalari et al and Curcio et al [24,25] adopted subjective assessment results of experiments using a tile-based streaming system for OV.…”

Section: Mobile Information Systemsmentioning

confidence: 99%

Mobile Edge Assisted Live Streaming System for Omnidirectional Video

Quan

Guo

et al. 2019

Mobile Information Systems

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As a popular form of virtual reality (VR) media, omnidirectional video (OV) has been continuously developed in recent years. OV contains the view of the scene in every direction, which will ask for around 120 Mbps with 8k resolution and 25 fps (frames per second). Although there has been a lot of work to optimize the transmission for on-demand of OV, the research on the live streaming of OV is still very lacking. Another big challenge for the OV live streaming system is the huge demand for computing resources. The existing terminal devices are difficult to completely carry tasks such as stitching, encoding, and rendering. This paper proposes a mobile edge assisted live streaming system for omnidirectional video (MELiveOV); the MELiveOV can intelligently offload the processing tasks to the edge computing enabled 5G base stations. The MELiveOV consists of an omnidirectional video generation module, a streaming module, and a viewpoint prediction module. A prototype system of MELiveOV is implemented to prove its complete end-to-end OV live streaming service. Evaluation result demonstrates that compared with the traditional solution, MELiveOV can reduce the network bandwidth requirement by about 50% and the transmission delay of more than 70% while ensuring the quality of the user’s experience.

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“…The viewport-dependent streaming model dramatically reduces the required bitrate, achieving bandwidth savings up to 40% [16]. These savings can be further improved with the help of additional practices, such as using different tiling schemes, predicting tiles that will be viewed [23] or using unequal quality levels for each eye in case of stereoscopic video [24]. On the other hand, the viewport-dependent model introduces a new problem of motion-to-high quality delay.…”

Section: Figure 2 Example Of Standard Streaming Framework For Omnidirectional Content [2]mentioning

confidence: 99%

Analysis of User Exploration Patterns during Scene Cuts in Omnidirectional Videos

Monakhov¹,

Naik²,

Curcio³

et al. 2018

Smpte 2018

Self Cite

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Video content is usually represented as a sequence of scenes joined together. Two adjacent scenes can share the same semantic content, similar to filming the scene from different angles, or they can describe semantically different content. The methods that switch between two adjacent scenes are called scene transitions. In the case when two scenes are just concatenated with no additional effects, the transition is called a scene cut. The scene transition is a vital instrument for guiding user's attention in classical cinema, but the impact of scene transitions becomes more relevant in a 360° video environment. During the scene transition, the user loses his/her previous interest point, that may lead to a change in the exploration behavior and affect the content delivery system, diminishing the viewing experience of the user. In this work, we have studied how the user exploration behavior changes in terms of the exploration range and angular speed metrics, and we have investigated whether this change of exploration behavior is different when the scene cut is within the same semantic content compared to the semantically different scenes.We conducted an experiment with 20 test subjects. The experiment consisted of two sets of videos. The first set included eight 20 second videos that were semantically different from each other. The videos were stitched together in a temporal domain using scene cuts. The second set was comprised of three videos with 4-5 scene cuts in each of them. The shots between the cuts were semantically consistent. We collected the positional data of head-mounted displays and converted it into the defined metrics, as per above explanation. Our research showed an increase in exploratory behavior and also revealed that there was a delay between the scene transition and the start of the exploration. The results were attested using t-test procedures. We have also shown that the exploratory behavior is dominant in the inter-scene transitions compared to the intra-scene transitions.

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Bandwidth Reduction of Omnidirectional Viewport-Dependent Video Streaming via Subjective Quality Assessment

Cited by 29 publications

References 9 publications

A Survey on 360-Degree Video: Coding, Quality of Experience and Streaming

A Survey on 360-Degree Video: Coding, Quality of Experience and Streaming

Mobile Edge Assisted Live Streaming System for Omnidirectional Video

Analysis of User Exploration Patterns during Scene Cuts in Omnidirectional Videos

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