A systematic literature review on video transcoding acceleration: challenges, solutions, and trends.
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| Title: | A systematic literature review on video transcoding acceleration: challenges, solutions, and trends. |
|---|---|
| Authors: | Borges, Alex1 (AUTHOR) amborges@inf.ufpel.edu.br, Zatt, Bruno1 (AUTHOR), Porto, Marcelo1 (AUTHOR), Correa, Guilherme1 (AUTHOR) |
| Source: | Multimedia Tools & Applications. Jul2024, Vol. 83 Issue 24, p64079-64108. 30p. |
| Subjects: | Machine learning, Video codecs, Internet traffic, Internet content, Streaming video & television, Video coding |
| Abstract: | Audiovisual productions currently dominate internet content, accounting for approximately 82% of online traffic in 2022. With the popularization of adaptive video streaming over the internet, transcoding has become an essential task to allow for bitrate adaptation and compatibility between servers and client devices that support various standards and formats. However, such conversion presents a high computational cost due to its cascade features, which sequentially runs the video decoding and re-encoding processes. This high cost exists especially due to the various encoding mode possibilities allowed in video codecs, mainly in recent, highly efficient standards and formats. On the other hand, the cascade transcoder model allows the possibility of inheriting information from the original bitstream, which can be used to accelerate the re-encoding process. This survey presents a systematic literature review of the main works published in the literature that propose transcoding acceleration methods for the main video coding standards and formats developed in the last decades. The majority of the works focus on both homogeneous and heterogeneous transcoding for the MPEG-2, H.264/AVC, H.265/HEVC, H.266/VVC, VP8, VP9, and AV1 formats and standards, and are based on heuristics and prediction models trained with machine learning algorithms. Based on the systematic literature review, a classification of the works according to the transcoding type and the methodology employed for acceleration is presented. The results obtained in each solution are compared in terms of complexity reduction and compression efficiency, and future trends on the field are discussed. [ABSTRACT FROM AUTHOR] |
| Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 178996636 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A systematic literature review on video transcoding acceleration: challenges, solutions, and trends. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Borges%2C+Alex%22">Borges, Alex</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> amborges@inf.ufpel.edu.br</i><br /><searchLink fieldCode="AR" term="%22Zatt%2C+Bruno%22">Zatt, Bruno</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Porto%2C+Marcelo%22">Porto, Marcelo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Correa%2C+Guilherme%22">Correa, Guilherme</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. Jul2024, Vol. 83 Issue 24, p64079-64108. 30p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Video+codecs%22">Video codecs</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+traffic%22">Internet traffic</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+content%22">Internet content</searchLink><br /><searchLink fieldCode="DE" term="%22Streaming+video+%26+television%22">Streaming video & television</searchLink><br /><searchLink fieldCode="DE" term="%22Video+coding%22">Video coding</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Audiovisual productions currently dominate internet content, accounting for approximately 82% of online traffic in 2022. With the popularization of adaptive video streaming over the internet, transcoding has become an essential task to allow for bitrate adaptation and compatibility between servers and client devices that support various standards and formats. However, such conversion presents a high computational cost due to its cascade features, which sequentially runs the video decoding and re-encoding processes. This high cost exists especially due to the various encoding mode possibilities allowed in video codecs, mainly in recent, highly efficient standards and formats. On the other hand, the cascade transcoder model allows the possibility of inheriting information from the original bitstream, which can be used to accelerate the re-encoding process. This survey presents a systematic literature review of the main works published in the literature that propose transcoding acceleration methods for the main video coding standards and formats developed in the last decades. The majority of the works focus on both homogeneous and heterogeneous transcoding for the MPEG-2, H.264/AVC, H.265/HEVC, H.266/VVC, VP8, VP9, and AV1 formats and standards, and are based on heuristics and prediction models trained with machine learning algorithms. Based on the systematic literature review, a classification of the works according to the transcoding type and the methodology employed for acceleration is presented. The results obtained in each solution are compared in terms of complexity reduction and compression efficiency, and future trends on the field are discussed. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-023-17862-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 64079 Subjects: – SubjectFull: Machine learning Type: general – SubjectFull: Video codecs Type: general – SubjectFull: Internet traffic Type: general – SubjectFull: Internet content Type: general – SubjectFull: Streaming video & television Type: general – SubjectFull: Video coding Type: general Titles: – TitleFull: A systematic literature review on video transcoding acceleration: challenges, solutions, and trends. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Borges, Alex – PersonEntity: Name: NameFull: Zatt, Bruno – PersonEntity: Name: NameFull: Porto, Marcelo – PersonEntity: Name: NameFull: Correa, Guilherme IsPartOfRelationships: – BibEntity: Dates: – D: 21 M: 07 Text: Jul2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 83 – Type: issue Value: 24 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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