A regression method for real-time video quality evaluation

M. Torres Vega; D.C. Mocanu; A. Liotta

doi:10.1145/3007120.3007125

A regression method for real-time video quality evaluation

M. Torres Vega, D.C. Mocanu, A. Liotta

Electro-Optical Communication

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

2 Citaten (Scopus)

380 Downloads (Pure)

Samenvatting

No-Reference (NR) metrics provide a mechanism to assess video quality in an ever-growing wireless network. Their low computational complexity and functional characteristics make them the primary choice when it comes to realtime content management and mobile streaming control. Unfortunately, common NR metrics suer from poor accuracy, particularly in network-impaired video streams. In this work, we introduce a regression-based video quality metric that is simple enough for real-time computation on thin clients, and comparably as accurate as state-of-the-art Full-Reference (FR) metrics, which are functionally and computationally inviable in real-time streaming. We benchmark our metric against the FR metric VQM (Video Quality Metric), finding a very strong correlation factor.

Originele taal-2	Engels
Titel	MoMM '16 : Proceedings of the 14th International Conference on Advances in Mobile Computing and Multimedia, 28-30 November 2016, Singapore, Singapore
Redacteuren	B. Abdulrazak, E. Pardede, M. Steinbauer, I. Khalil, G. Anderst-Kotsis
Plaats van productie	New York
Uitgeverij	Association for Computing Machinery, Inc.
Pagina's	217-224
Aantal pagina's	8
ISBN van geprinte versie	978-1-4503-4806-5
DOI's	https://doi.org/10.1145/3007120.3007125
Status	Gepubliceerd - 29 nov. 2016
Evenement	14th International Conference on Advances in Mobile Computing & Multimedia (MoMM2016) - Singapore, Singapore Duur: 28 nov. 2016 → 30 nov. 2016 Congresnummer: 14 http://www.iiwas.org/conferences/momm2016/

Congres

Congres	14th International Conference on Advances in Mobile Computing & Multimedia (MoMM2016)
Verkorte titel	MOMM2016
Land/Regio	Singapore
Stad	Singapore
Periode	28/11/16 → 30/11/16
Internet adres	http://www.iiwas.org/conferences/momm2016/

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10.1145/3007120.3007125

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Torres Vega, M., Mocanu, D. C., & Liotta, A. (2016). A regression method for real-time video quality evaluation. In B. Abdulrazak, E. Pardede, M. Steinbauer, I. Khalil, & G. Anderst-Kotsis (editors), MoMM '16 : Proceedings of the 14th International Conference on Advances in Mobile Computing and Multimedia, 28-30 November 2016, Singapore, Singapore (blz. 217-224). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3007120.3007125

Torres Vega, M. ; Mocanu, D.C. ; Liotta, A. / A regression method for real-time video quality evaluation. MoMM '16 : Proceedings of the 14th International Conference on Advances in Mobile Computing and Multimedia, 28-30 November 2016, Singapore, Singapore. redacteur / B. Abdulrazak ; E. Pardede ; M. Steinbauer ; I. Khalil ; G. Anderst-Kotsis. New York : Association for Computing Machinery, Inc., 2016. blz. 217-224

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abstract = "No-Reference (NR) metrics provide a mechanism to assess video quality in an ever-growing wireless network. Their low computational complexity and functional characteristics make them the primary choice when it comes to realtime content management and mobile streaming control. Unfortunately, common NR metrics suer from poor accuracy, particularly in network-impaired video streams. In this work, we introduce a regression-based video quality metric that is simple enough for real-time computation on thin clients, and comparably as accurate as state-of-the-art Full-Reference (FR) metrics, which are functionally and computationally inviable in real-time streaming. We benchmark our metric against the FR metric VQM (Video Quality Metric), finding a very strong correlation factor.",

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Torres Vega, M, Mocanu, DC & Liotta, A 2016, A regression method for real-time video quality evaluation. in B Abdulrazak, E Pardede, M Steinbauer, I Khalil & G Anderst-Kotsis (uitgave), MoMM '16 : Proceedings of the 14th International Conference on Advances in Mobile Computing and Multimedia, 28-30 November 2016, Singapore, Singapore. Association for Computing Machinery, Inc., New York, blz. 217-224, 14th International Conference on Advances in Mobile Computing & Multimedia (MoMM2016)
, Singapore, Singapore, 28/11/16. https://doi.org/10.1145/3007120.3007125

A regression method for real-time video quality evaluation. / Torres Vega, M.; Mocanu, D.C.; Liotta, A.
MoMM '16 : Proceedings of the 14th International Conference on Advances in Mobile Computing and Multimedia, 28-30 November 2016, Singapore, Singapore. uitgave / B. Abdulrazak; E. Pardede; M. Steinbauer; I. Khalil; G. Anderst-Kotsis. New York: Association for Computing Machinery, Inc., 2016. blz. 217-224.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AB - No-Reference (NR) metrics provide a mechanism to assess video quality in an ever-growing wireless network. Their low computational complexity and functional characteristics make them the primary choice when it comes to realtime content management and mobile streaming control. Unfortunately, common NR metrics suer from poor accuracy, particularly in network-impaired video streams. In this work, we introduce a regression-based video quality metric that is simple enough for real-time computation on thin clients, and comparably as accurate as state-of-the-art Full-Reference (FR) metrics, which are functionally and computationally inviable in real-time streaming. We benchmark our metric against the FR metric VQM (Video Quality Metric), finding a very strong correlation factor.

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Torres Vega M, Mocanu DC, Liotta A. A regression method for real-time video quality evaluation. In Abdulrazak B, Pardede E, Steinbauer M, Khalil I, Anderst-Kotsis G, redacteurs, MoMM '16 : Proceedings of the 14th International Conference on Advances in Mobile Computing and Multimedia, 28-30 November 2016, Singapore, Singapore. New York: Association for Computing Machinery, Inc. 2016. blz. 217-224 doi: 10.1145/3007120.3007125

A regression method for real-time video quality evaluation

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