Szczegóły publikacji
Opis bibliograficzny
Top-down and bottom-up approaches to video quality of experience studies; overview and proposal of a new model / Kamil KONIUCH, Sabina Baraković, Jasmina Baraković Husić, Sruti Subramanian, Katrien De Moor, Lucjan JANOWSKI, Michał Wierzchoń // Frontiers in Computer Science [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2624-9898. — 2024 — vol. 6 art. no. 1305670, s. 01-09. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 08-09, Abstr. — Publikacja dostępna online od: 2024-04-15
Autorzy (7)
- AGHKoniuch Kamil
- Baraković Sabina
- Baraković Husić Jasmina
- Subramanian Sruti
- De Moor Katrien
- AGHJanowski Lucjan
- Wierzchoń Michał
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 153518 |
|---|---|
| Data dodania do BaDAP | 2024-06-12 |
| Tekst źródłowy | URL |
| DOI | 10.3389/fcomp.2024.1305670 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Frontiers in Computer Science |
Abstract
Modern video streaming services require quality assurance of the presented audiovisual material. Quality assurance mechanisms allow streaming platforms to provide quality levels that are considered sufficient to yield user satisfaction, with the least possible amount of data transferred. A variety of measures and approaches have been developed to control video quality, e.g., by adapting it to network conditions. These include objective matrices of the quality and thresholds identified by means of subjective perceptual judgments. The former group of matrices has recently gained the attention of (multi) media researchers. They call this area of study “Quality of Experience” (QoE). In this paper, we present a theoretical model based on review of previous QoE’s models. We argue that most of them represent the bottom-up approach to modeling. Such models focus on describing as many variables as possible, but with a limited ability to investigate the causal relationship between them; therefore, the applicability of the findings in practice is limited. To advance the field, we therefore propose a structural, top-down model of video QoE that describes causal relationships among variables. This novel top-down model serves as a practical guide for structuring QoE experiments, ensuring the incorporation of influential factors in a confirmatory manner.
