Fuzzy and ISODATA classification of face contours

Author

Gu, W.A. ; Su, Guang-Da ; Du, Cheng

Author_Institution

Dept. of Electron. Eng., Tsinghua Univ., Beijing, China

Volume

6

fYear

2004

fDate

26-29 Aug. 2004

Firstpage

3568

Abstract

A method derived from fuzzy and ISODATA clustering algorithm is proposed to classify face contours. An improved ASM method is used to get face contours as one of face shape features. By using the modified ISODATA method based on Hausdorff distance, which is more suitable to classify "shape" features, face contours are clustering into 7 classes. Then the fuzzy c-mean clustering method is used to fuzzy categorize the face contours into different classes. Experiment shows that this clustering approach could automatic classify the human face contours fast and reasonably. Moreover, it could help to accelerate the speed of face recognition and improve the accuracy of face recognition.

Keywords

face recognition; pattern clustering; ISODATA clustering algorithm; active shape model; face contours classification; face recognition; fuzzy c-mean clustering method; Acceleration; Active shape model; Clustering algorithms; Clustering methods; Data mining; Face detection; Face recognition; Feature extraction; Humans; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on

Print_ISBN

0-7803-8403-2

Type

conf

DOI

10.1109/ICMLC.2004.1380408

Filename

1380408