FAUST: Fast Per-Scene Encoding Using Entropy-Based Scene Detection and Machine Learning

HTTP adaptive video streaming is a widespread and sought-after technology on the Internet that allows clients to dynamically switch between different stream qualities presented in the bitrate ladder to optimize overall received video quality. Currently, there exist several approaches of different co...

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Bibliographic Details
Main Authors:	Anatoliy Zabrovskiy, Prateek Agrawal, Christian Timmerer, Radu Prodan
Format:	article
Language:	EN
Published:	FRUCT 2021
Subjects:	per-title encoding per-shot encoding scene detection video entropy neural networks video encoding video transcoding http adaptive streaming mpeg-dash Telecommunication TK5101-6720
Online Access:	https://doaj.org/article/2c4ff9718dd84364864e573ee8909ef5
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FAUST: Fast Per-Scene Encoding Using Entropy-Based Scene Detection and Machine Learning

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