OBJECTIVE VIDEO QUALITY COMPARISON OF USER-GENERATED CONTENT PLATFORMS

Uploading videos to platforms for sharing has been a core feature of the internet for nearly two decades. Advances in video encoding algorithms, their standardization, and increased computational power have significantly improved the visual quality of online videos. This paper evaluates the video quality across several popular platforms, including YouTube, Facebook, and Vimeo. Using three test sequences with varying content characteristics, the study employs full-reference objective video quality metrics—VMAF, PSNR-HVS-M, and MS-SSIM—to assess video quality at resolutions supported by all platforms. The results provide insights into the comparative performance of each platform in delivering high-quality video

Authors

Publication Details

Published
2024-10-22
DOI
https://doi.org/10.24867/grid-2024-p24
Primary Topic
Image and Video Quality Assessment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

OBJECTIVE VIDEO QUALITY COMPARISON OF USER-GENERATED CONTENT PLATFORMS

Jaroslav Svoboda
Image and Video Quality Assessment
article

OBJECTIVE VIDEO QUALITY COMPARISON OF USER-GENERATED CONTENT PLATFORMS

Jaroslav Svoboda
article en

Abstract

Uploading videos to platforms for sharing has been a core feature of the internet for nearly two decades. Advances in video encoding algorithms, their standardization, and increased computational power have significantly improved the visual quality of online videos. This paper evaluates the video quality across several popular platforms, including YouTube, Facebook, and Vimeo. Using three test sequences with varying content characteristics, the study employs full-reference objective video quality metrics—VMAF, PSNR-HVS-M, and MS-SSIM—to assess video quality at resolutions supported by all platforms. The results provide insights into the comparative performance of each platform in delivering high-quality video

Openalex Percentile: Top 82%
Image and Video Quality Assessment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

OBJECTIVE VIDEO QUALITY COMPARISON OF USER-GENERATED CONTENT PLATFORMS — Jaroslav Svoboda · (2024) | TGRS Research Map | TGRS