A Framework for Weighted Fusion of Multiple Statistical Models of Shape and Appearance

Author

Butakoff, C. ; Frangi, A.F.

Author_Institution

Dept. of Technol., Univ. Pompeu Fabra, Barcelona

Volume

28

Issue

11

fYear

2006

Firstpage

1847

Lastpage

1857

Abstract

This paper presents a framework for weighted fusion of several active shape and active appearance models. The approach is based on the eigenspace fusion method proposed by Hall et al., which has been extended to fuse more than two weighted eigenspaces using unbiased mean and covariance matrix estimates. To evaluate the performance of fusion, a comparative assessment on segmentation precision as well as facial verification tests are performed using the AR, EQUINOX, and XM2VTS databases. Based on the results, it is concluded that the fusion is useful when the model needs to be updated online or when the original observations are absent

Keywords

computer vision; covariance matrices; statistical analysis; AR databases; EQUINOX databases; XM2VTS databases; active appearance models; covariance matrix; eigenspace fusion method; facial verification tests; multiple statistical models; unbiased mean; weighted fusion; Active appearance model; Active shape model; Context modeling; Covariance matrix; Databases; Fuses; Image analysis; Jacobian matrices; Shape control; Testing; AAM; ASM; model fusion; segmentation.; statistical model; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Simulation; Face; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical; Pattern Recognition, Automated; Subtraction Technique;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/TPAMI.2006.215

Filename

1704839