AAM fitting using shape parameter distribution

Youhei Shiraishi*, Shinya Fujie, Tetsunori Kobayashi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


A novel constraint using shape parameter distribution into the AAM fitting method is proposed. Active appearance models (AAMs) are some of the most popular facial models. AAM-based face tracking delivers accurate alignment results. However, non-face-like shapes can also be estimated by AAMs, unlike by the conventional AAM fitting method, which only minimizes the matching error of the image. This is one of the causes for face tracking performance degradation in AAMs. A constraint using the shape parameter distribution is added in order to solve this problem.

Original languageEnglish
Title of host publicationProceedings of the 20th European Signal Processing Conference, EUSIPCO 2012
Number of pages5
Publication statusPublished - 2012
Event20th European Signal Processing Conference, EUSIPCO 2012 - Bucharest, Romania
Duration: 2012 Aug 272012 Aug 31

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491


Conference20th European Signal Processing Conference, EUSIPCO 2012


  • Active appearance models
  • Face tracking
  • Inverse compositional image alignment

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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