Robust Active Appearance Model Matching

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Article , Conference object 01 Jan 2005Publisher:Springer Berlin Heidelberg

Authors: Reinhard Beichel; Horst Bischof; Franz Leberl; Milan Sonka;

doi: 10.1007/11505730_10

pmid: 17354689

Robust Active Appearance Model Matching

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Abstract

A novel robust active appearance model (AAM) matching algorithm is presented. The method consists of two main stages. First, initial residuals are clustered by a non parametric mean shift mode detection step. Second, modes without gross outliers are selected using an objective function. Robustness of the matching procedure is demonstrated on a variety of examples with different noise conditions. The proposed algorithm outperformed the conventional AAM matching on images with gross disturbances and can tolerate up to 40% of disturbed data.

Related Organizations

Graz University of Technology
Austria
University of Iowa
United States

Keywords

Reproducibility of Results, Models, Biological, Sensitivity and Specificity, Pattern Recognition, Automated, Radiographic Image Enhancement, Finger Phalanges, Artificial Intelligence, Subtraction Technique, Cluster Analysis, Humans, Radiographic Image Interpretation, Computer-Assisted, Computer Simulation, Algorithms

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