Fast Partitioning Decision Making for Prediction Units on H.264-to-HEVC Transcoding Using Machine Learning

  • Yan Soares UFPel
  • Guilherme Corrêa UFPel
  • Luciano Agostini UFPel

Resumo


With the high computational complexity of transcoding video from the H.264/AVC standard to the state-of-the-art High Efficiency Video Coding (HEVC) standard, new approaches must be explored to fasten up the adaptation of all legacy content. This work proposes a fast decision algorithm to reduce the transcoding complexity between the H.264/AVC and HEVC video standards using partitioning information from the H.264/AVC macroblocks to fasten up the partitioning decisions of Prediciton Units (PUs) on the HEVC reencoding process. This strategy allowed a 25% reduction on transcoding time with a compression efficiency loss of just 0.745% in comparison with the original transcoder.
Publicado
29/10/2019
Como Citar

Selecione um Formato
SOARES, Yan; CORRÊA, Guilherme; AGOSTINI, Luciano. Fast Partitioning Decision Making for Prediction Units on H.264-to-HEVC Transcoding Using Machine Learning. In: BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA), 25. , 2019, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 161-168.