Rate Assignment in 360-Degree Video Tiled Streaming Using Random Forest Regression
Robert Skupin, Kai Bitterschulte, Yago Sanchez, Cornelius Hellge, Thomas Schierl
Abstract
Streaming of high-resolution 360-degree video is typically done in a viewport-dependent fashion such as in the tile-based viewport-dependent profile of MPEG OMAF wherein clients continuously adapt their tile selection according to the user viewport. From the perspective of a streaming service operator, tile rate assignment is crucial to ensure that a given target bitrate is obeyed while quality distribution among tiles leads to a favorable user experience. This paper addresses rate assignment in a distributed tile encoding system for such multi-resolution tiled streaming services based on the emerging Versatile Video Coding Standard. A model for rate assignment is derived based on random forest regression using spatio-temporal activity and encodings of a learning dataset.
BibTeX
@inproceedings{icassp2020_rateassignmentin,
title = {Rate Assignment in 360-Degree Video Tiled Streaming Using Random Forest Regression},
author = {Robert Skupin and Kai Bitterschulte and Yago Sanchez and Cornelius Hellge and Thomas Schierl},
booktitle = {ICASSP 2020},
year = {2020}
}