A Hybrid Algorithm of Facial Feature Point Location Based on Improved MR-ASM and AAM

Author

Sicong, Zhang ; Lifang, Wu ; Xiaoguang, He ; Jie, Tian

Author_Institution

Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol.

Volume

3

fYear

2006

fDate

16-20 Nov. 2006

Abstract

Accurate and robust location of feature point is a difficult and complicated issue in face recognition. This paper proposes a facial feature point location algorithm based on improved multi-resolution-active shape models (MR-ASM) and active appearance models (AAM). There are three main achievements of our algorithm: 1, we unify MR-ASM and AAM together to improve facial feature point location. 2, AAM is improved so that it has the same implementation framework as ASM. 3, the MR-ASM is adjusted to figure out more robust parameters. Experimental results prove that our algorithm is more accurate than traditional MR-ASM

Keywords

face recognition; feature extraction; image resolution; AAM; MR-ASM; active appearance models; face recognition; facial feature point location; multiresolution-active shape models; Active appearance model; Active shape model; Data mining; Face recognition; Facial features; Flowcharts; Image resolution; Labeling; Principal component analysis; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.345774

Filename

4129205