Content dependent spatial resolution selection for MPEG DASH segmentation

Vlaovic, Jelena; Rimac-Drlje, Snježana; Žagar, Drago; Filipović, Luka

doi:10.1016/j.jii.2021.100240

Cited by 3 publications

(5 citation statements)

References 30 publications

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“…Based on the obtained curves, a model for selecting optimal switching points to a higher spatial resolution was developed and presented in [35].…”

Section: Test Setupmentioning

confidence: 99%

“…To improve the segmentation process even further, the model for selecting the optimal number of representations and bitrates while eliminating the need for precoding is proposed in this paper. Based on the obtained curves, a model for selecting optimal switching points to a higher spatial resolution was developed and presented in [35].…”

Section: Test Setupmentioning

confidence: 99%

“…Equation ( 4) is used for both A(SITI) and B(SITI), but with different parameters, X and Y. SITI has proven to be an adequate measure that can be used to describe the spatial and temporal activity of video sequences and consequently their encoding complexity [35]. The nonlinear least-squares curve-fitting was done using the lscurvefit function in Matlab and the resulting coefficients X and Y, as well as PLCC values, are given in Table 4.…”

Section: ( ) = • ( ) +mentioning

confidence: 99%

“…The nonlinear least-squares curve-fitting was done using the lscurvefit function in Matlab and the resulting coefficients X and Y, as well as PLCC values, are given in Table 4. For the correct application of this model, the optimal spatial resolution for the given bitrate and SITI must be selected according to Equation (6) presented in [35].…”

Section: ( ) = • ( ) +mentioning

confidence: 99%

“…For the correct application of this model, the optimal spatial resolution for the given bitrate and SITI must be selected according to Equation (6) presented in [35].…”

Section: ( ) = • ( ) +mentioning

confidence: 99%

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Content Dependent Representation Selection Model for Systems Based on MPEG DASH

2021

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A standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) ensures the interoperability between different streaming services and the highest possible video quality in changing network conditions. The solutions described in the available literature that focus on video segmentation are mostly proprietary, use a high amount of computational power, lack the methodology, model notation, information needed for reproduction, or do not consider the spatial and temporal activity of video sequences. This paper presents a new model for selecting optimal parameters and number of representations for video encoding and segmentation, based on a measure of the spatial and temporal activity of the video content. The model was developed for the H.264 encoder, using Structural Similarity Index Measure (SSIM) objective metrics as well as Spatial Information (SI) and Temporal Information (TI) as measures of video spatial and temporal activity. The methodology that we used to develop the mathematical model is also presented in detail so that it can be applied to adapt the mathematical model to another type of an encoder or a set of encoding parameters. The efficiency of the segmentation made by the proposed model was tested using the Basic Adaptation algorithm (BAA) and Segment Aware Rate Adaptation (SARA) algorithm as well as two different network scenarios. In comparison to the segmentation available in the relevant literature, the segmentation based on the proposed model obtains better SSIM values in 92% of cases and subjective testing showed that it achieves better results in 83.3% of cases.

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“…Based on the obtained curves, a model for selecting optimal switching points to a higher spatial resolution was developed and presented in [35].…”

Section: Test Setupmentioning

confidence: 99%

Section: Test Setupmentioning

confidence: 99%

Section: ( ) = • ( ) +mentioning

confidence: 99%

Section: ( ) = • ( ) +mentioning

confidence: 99%

“…For the correct application of this model, the optimal spatial resolution for the given bitrate and SITI must be selected according to Equation (6) presented in [35].…”

Section: ( ) = • ( ) +mentioning

confidence: 99%

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Content Dependent Representation Selection Model for Systems Based on MPEG DASH

2021

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Cloud‐based video streaming services: Trends, challenges, and opportunities

Kumar,

Sharma,

Tanwar

et al. 2024

CAAI Trans on Intel Tech

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Cloud computing has drastically changed the delivery and consumption of live streaming content. The designs, challenges, and possible uses of cloud computing for live streaming are studied. A comprehensive overview of the technical and business issues surrounding cloud‐based live streaming is provided, including the benefits of cloud computing, the various live streaming architectures, and the challenges that live streaming service providers face in delivering high‐quality, real‐time services. The different techniques used to improve the performance of video streaming, such as adaptive bit‐rate streaming, multicast distribution, and edge computing are discussed and the necessity of low‐latency and high‐quality video transmission in cloud‐based live streaming is underlined. Issues such as improving user experience and live streaming service performance using cutting‐edge technology, like artificial intelligence and machine learning are discussed. In addition, the legal and regulatory implications of cloud‐based live streaming, including issues with network neutrality, data privacy, and content moderation are addressed. The future of cloud computing for live streaming is examined in the section that follows, and it looks at the most likely new developments in terms of trends and technology. For technology vendors, live streaming service providers, and regulators, the findings have major policy‐relevant implications. Suggestions on how stakeholders should address these concerns and take advantage of the potential presented by this rapidly evolving sector, as well as insights into the key challenges and opportunities associated with cloud‐based live streaming are provided.

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Fast Content Adaptive Representation Selection in HEVC-Based Video Coding for Streaming Applications

Suljug

Rimac-Drlje

2022

2022 International Symposium ELMAR

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Content dependent spatial resolution selection for MPEG DASH segmentation

Cited by 3 publications

References 30 publications

Content Dependent Representation Selection Model for Systems Based on MPEG DASH

Content Dependent Representation Selection Model for Systems Based on MPEG DASH

Cloud‐based video streaming services: Trends, challenges, and opportunities

Fast Content Adaptive Representation Selection in HEVC-Based Video Coding for Streaming Applications

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