Title :
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.
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;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345774