Multi-Component/Multi-Model AAM framework for face image modeling

  • Muhammad Aurangzeb Khan
  • , Costas S. Xydeas
  • , Hassan Ahmed

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

Abstract

An image face modeling framework is proposed that aims to enhance the face modeling capability of the well known Active Appearance Model (AAM). AAM has been used successfully in person-specific related applications but it poses significant limitations when employed in generic face modeling. Thus this work is focused on the development of new face models which are generic in nature and which accurately fit unseen image faces, both in terms of shape and texture. For this purpose, images are decomposed into face related components which are subsequently clustered on the basis of shape similarities. Experimental results show that models generated through this novel framework can be significantly more effective than conventional AAM, in terms of both shape and texture.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Subtitle of host publicationProceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages2124-2128
Number of pages5
ISBN (Electronic)9781479903566
DOIs
Publication statusPublished - 21 Oct 2013
Event2013 IEEE International Conference on Acoustics, Speech, and Signal Processing - Vancouver, Canada
Duration: 26 May 201331 May 2013

Publication series

NameProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
PublisherIEEE
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

Conference2013 IEEE International Conference on Acoustics, Speech, and Signal Processing
Country/TerritoryCanada
CityVancouver
Period26/05/1331/05/13

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