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Rate Assignment in 360-Degree Video Tiled Streaming Using Random Forest Regression

: Skupin, R.; Bitterschulte, K.; Sanchez, Y.; Hellge, C.; Schierl, T.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society; IEEE Signal Processing Society:
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020. Proceedings : May 4-8, 2020, Barcelona, Spain
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-5090-6631-5
ISBN: 978-1-5090-6632-2
International Conference on Acoustics, Speech and Signal Processing (ICASSP) <45, 2020, Barcelona>
Conference Paper
Fraunhofer HHI ()

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.