title: Fast active appearance model search using canonical correlation analysis.
abstract: A fast AAM search algorithm based on canonical correlation analysis (CCA-AAM) is introduced. It efficiently models the dependency between texture residuals and model parameters during search. Experiments show that CCA-AAMs, while requiring similar implementation effort, consistently outperform standard search with regard to convergence speed by a factor of four.
authors.affiliation: Pattern Recognition and Image Processing Group, Institute of Computer Aided Automation, Vienna University of Technology, Favoritenstr. 9/183/2, A-1040 Vienna, Austria. donner@prip.tuwien.ac.at
authors.forename: René
authors.initials: R
authors.lastname: Donner
authors.forename: Michael
authors.initials: M
authors.lastname: Reiter
authors.forename: Georg
authors.initials: G
authors.lastname: Langs
authors.forename: Philipp
authors.initials: P
authors.lastname: Peloschek
authors.forename: Horst
authors.initials: H
authors.lastname: Bischof
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D013223:Statistics as Topic