Efficient motion vector re-estimation based on a novel cost model for a H.264/AVC transcoder

Soongi Hong, Yoonsik Choe, Yong Goo Kim

Research output: Contribution to journalArticle

Abstract

In transcoding, it is well known that refinement of the motion vectors is critical to enhance the quality of transcoded video while significantly reducing transcoding complexity. This paper proposes a novel cost model to estimate the rate-distortion cost of motion vector composition in order to develop a reliable motion vector re-estimation method that has reasonable computation cost. Based on a statistical analysis of motion compensated prediction errors, we design a basic form of the proposed cost model as a function of distance from the optimal motion vector. Simulations with a transcoder employing the proposed cost model demonstrate a significant quality gain over representative video transcoding schemes with no complexity increase.

Original languageEnglish
Pages (from-to)777-780
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE99D
Issue number3
DOIs
Publication statusPublished - 2016 Mar

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All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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