Pregled bibliografske jedinice broj: 1139411
Content Dependent Representation Selection Model for Systems Based on MPEG DASH
Content Dependent Representation Selection Model for Systems Based on MPEG DASH // Electronics, 10 (2021), 15; 1843, 17 doi:10.3390/electronics10151843 (međunarodna recenzija, članak, znanstveni)
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Naslov
Content Dependent Representation Selection Model
for Systems Based on MPEG DASH
Autori
Vlaović, Jelena ; Rimac-Drlje, Snježana ; Žagar, Drago
Izvornik
Electronics (2079-9292) 10
(2021), 15;
1843, 17
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
adaptive streaming ; MPEG DASH ; video segmentation ; representation ; methodology ; spatial information ; temporal information ; MOS ; SSIM
Sažetak
A standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) ensures the interoperability between different streaming services and the highest possible video quality in changing network conditions. The solutions described in the available literature that focus on video segmentation are mostly proprietary, use a high amount of computational power, lack the methodology, model notation, information needed for reproduction, or do not consider the spatial and temporal activity of video sequences. This paper presents a new model for selecting optimal parameters and number of representations for video encoding and segmentation, based on a measure of the spatial and temporal activity of the video content. The model was developed for the H.264 encoder, using Structural Similarity Index Measure (SSIM) objective metrics as well as Spatial Information (SI) and Temporal Information (TI) as measures of video spatial and temporal activity. The methodology that we used to develop the mathematical model is also presented in detail so that it can be applied to adapt the mathematical model to another type of encoder or a set of encoding parameters. The efficiency of the segmentation made by the proposed model was tested using the Basic Adaptation algorithm (BAA) and Segment Aware Rate Adaptation (SARA) algorithm as well as two different network scenarios. In comparison to the segmentation available in the relevant literature, the segmentation based on the proposed model obtains better SSIM values in 92% of cases and subjective testing showed that it achieves better results in 83.3% of cases.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus