A regression method for real-time video quality evaluation

Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

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 suffer 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.

Original languageEnglish
Title of host publicationMoMM '16
Subtitle of host publicationProceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media
EditorsBessam Abdulrazak, Matthias Steinbauer, Ismail Khalil, Eric Pardede, Gabriele Anderst-Kotsis
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages217-224
Number of pages8
ISBN (Electronic)9781450348065
DOIs
Publication statusPublished - 28 Nov 2016
Externally publishedYes
Event14th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2016 - Grand Copthorne Waterfront Singapore, Singapore, Singapore
Duration: 28 Nov 201630 Nov 2016
Conference number: 14

Conference

Conference14th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2016
Abbreviated titleMoMM 2016
CountrySingapore
CitySingapore
Period28/11/1630/11/16

Keywords

  • Cognitive QoE assessment metrics
  • No-reference video quality
  • Quality of experience
  • Regression processes

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