Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics
Video traffic from content delivery networks occupied 82% of all consumed bandwidth in 2022. Nevertheless, the available bandwidth is sometimes volatile and limited. Adaptive video streaming or, in other words, prediction of quality is the key to increasing throughput and reducing storage. Unfortuna...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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FRUCT
2023-05-01
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| Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| Subjects: | |
| Online Access: | https://www.fruct.org/publications/volume-33/fruct33/files/Maz.pdf |
| _version_ | 1797807552084312064 |
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| author | Vladimir A Mazin Ksenia Nezhivleva Michael Cree Lee Streeter Anastasia Mozhaeva |
| author_facet | Vladimir A Mazin Ksenia Nezhivleva Michael Cree Lee Streeter Anastasia Mozhaeva |
| author_sort | Vladimir A Mazin |
| collection | DOAJ |
| description | Video traffic from content delivery networks occupied 82% of all consumed bandwidth in 2022. Nevertheless, the available bandwidth is sometimes volatile and limited. Adaptive video streaming or, in other words, prediction of quality is the key to increasing throughput and reducing storage. Unfortunately, while developing video quality metrics, a problem exists in the algorithmic representation of the human visual system, such as the cognitive component, namely the delay of human reaction to artifacts, which is not represented in the current works. The presented new methodology of data collection of the delay of the human visual system response to video artifacts in modern terms of providing information in natural conditions is presented. New knowledge of the human visual system adaptation or other words time of reaction of perception of artefacts, including the response to motion perceptions necessary for correct work of video quality assessments, is presented and tested. The proposed work introduced that the use of new data on the human visual system adaptation gives an improvement in the performance of video quality assessment metrics. |
| first_indexed | 2024-03-13T06:24:17Z |
| format | Article |
| id | doaj.art-ee373750dcad42f28b733999bc796e6d |
| institution | Directory Open Access Journal |
| issn | 2305-7254 2343-0737 |
| language | English |
| last_indexed | 2024-03-13T06:24:17Z |
| publishDate | 2023-05-01 |
| publisher | FRUCT |
| record_format | Article |
| series | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| spelling | doaj.art-ee373750dcad42f28b733999bc796e6d2023-06-09T11:41:51ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372023-05-0133119219710.23919/FRUCT58615.2023.10142993Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality MetricsVladimir A Mazin0Ksenia Nezhivleva1Michael Cree2Lee Streeter3Anastasia Mozhaeva4Moscow Technical University of Communications and InformaticsMoscow Technical University of Communications and InformaticsUniversity of WaikatoUniversity of WaikatoThe University of WaikatoVideo traffic from content delivery networks occupied 82% of all consumed bandwidth in 2022. Nevertheless, the available bandwidth is sometimes volatile and limited. Adaptive video streaming or, in other words, prediction of quality is the key to increasing throughput and reducing storage. Unfortunately, while developing video quality metrics, a problem exists in the algorithmic representation of the human visual system, such as the cognitive component, namely the delay of human reaction to artifacts, which is not represented in the current works. The presented new methodology of data collection of the delay of the human visual system response to video artifacts in modern terms of providing information in natural conditions is presented. New knowledge of the human visual system adaptation or other words time of reaction of perception of artefacts, including the response to motion perceptions necessary for correct work of video quality assessments, is presented and tested. The proposed work introduced that the use of new data on the human visual system adaptation gives an improvement in the performance of video quality assessment metrics.https://www.fruct.org/publications/volume-33/fruct33/files/Maz.pdfhuman visual system video quality assessment subjective quality motion perception video artefacts |
| spellingShingle | Vladimir A Mazin Ksenia Nezhivleva Michael Cree Lee Streeter Anastasia Mozhaeva Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics Proceedings of the XXth Conference of Open Innovations Association FRUCT human visual system video quality assessment subjective quality motion perception video artefacts |
| title | Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics |
| title_full | Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics |
| title_fullStr | Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics |
| title_full_unstemmed | Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics |
| title_short | Research and Application of the Adaptive Model of the Human Visual System for Improving the Effectiveness of Objective Video Quality Metrics |
| title_sort | research and application of the adaptive model of the human visual system for improving the effectiveness of objective video quality metrics |
| topic | human visual system video quality assessment subjective quality motion perception video artefacts |
| url | https://www.fruct.org/publications/volume-33/fruct33/files/Maz.pdf |
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