Year: 2024
Type: conference-paper
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
Author: Jaroslav Svoboda
Institution: Prague University of Economics and Business
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4403644489