Elastic Appearance Models

Mads Fogtmann Hansen, Jens Fagertun, Rasmus Larsen

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    This paper presents a fusion of the active appearance model (AAM) and the Riemannian elasticity framework which yields a non-linear shape model and a linear texture model – the active elastic appearance model (EAM). The non-linear elasticity shape model is more flexible than the usual linear subspace model, and it is therefore able to capture more complex shape variations. Local rotation and translation invariance are the primary explanation for the additional flexibility. In addition, we introduce global scale invariance into the Riemannian elasticity framework which together with the local translation and rotation invariances eliminate the need for separate pose estimation. The new approach was tested against AAM in three experiments; face labeling, face labeling with poor initialization and corpus callosum segmentation. In all the examples the EAM performed significantly better than AAM. Our Matlab implementation can be downloaded through svn from https://svn.imm.dtu.dk/AAMLab/svn/AAMLab/trunk/
    Original languageEnglish
    Title of host publicationProceedings of the British Machine Vision Conference
    PublisherBMVA Press
    Publication date2011
    ISBN (Print)1-901725-43-X
    Publication statusPublished - 2011
    Event22nd British Machine Vision Conference - Dundee, United Kingdom
    Duration: 29 Aug 20112 Sep 2011
    Conference number: 22


    Conference22nd British Machine Vision Conference
    CountryUnited Kingdom
    Internet address

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