title: Robust active appearance model matching.
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.
authors.affiliation: Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16/2, A-8010 Graz, Austria. beichel@icg.tu-graz.ac.at
authors.forename: Reinhard
authors.initials: R
authors.lastname: Beichel
authors.forename: Horst
authors.initials: H
authors.lastname: Bischof
authors.forename: Franz
authors.initials: F
authors.lastname: Leberl
authors.forename: Milan
authors.initials: M
authors.lastname: Sonka
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003198:Computer Simulation; D050278:Finger Phalanges / Q000000981:diagnostic imaging*; D006801:Humans; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique