A statistical approach to motion vector field smoothing for block-based motion-compensated frame interpolation

Dooseop Choi, Wonseok Song, Jongsoon Park, Hyuk Choi, Taejeong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper proposes a new approach to motion vector field smoothing for block-based motion-compensated frame interpolation (MCFI). Based on the assumption that an observed motion vector field, which is the result of a block-based motion estimation (BME), is a degraded version of the true motion vector field, we calculate the maximum a posteriori (MAP) estimate of the true motion vector field from the observed. The degradation and the true motion vector field are modeled as additive Gaussian noise and a Markov random field, respectively. Iterative conditional modes (ICM) method is used for calculating the MAP estimate. The experimental results show that the proposed algorithm not only smoothes MVFs but also preserves motion boundaries better than the existing methods.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages989-992
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: 25 Mar 201230 Mar 2012

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Country/TerritoryJapan
CityKyoto
Period25/03/1230/03/12

Keywords

  • MAPMRF
  • MCFI
  • Motion vector field smoothing

Fingerprint

Dive into the research topics of 'A statistical approach to motion vector field smoothing for block-based motion-compensated frame interpolation'. Together they form a unique fingerprint.

Cite this