DocumentCode :
2238893
Title :
A SOM-wavelet networks for face identification
Author :
Zhi, Yang ; Ming, Gu
Author_Institution :
Sch. of Software, Tsinghua Univ., Beijing, China
fYear :
2005
fDate :
6-8 July 2005
Abstract :
This paper describes a novel SOM-wavelet networks method for face recognition. We employed a SOM algorithm, which is based on the structure of a biological model, to extract shape feature of face. After the unsupervised learning, each face image will produce a shape-based vector named representative face. A wavelet network is applied to face identification to collect global information from a face image. Then we proposed a new approach to compute the similarity between two faces on both the global means and topological means. The experimental results are compared with other effective face identification methods and our proposed method showed a good performance.
Keywords :
face recognition; feature extraction; image representation; self-organising feature maps; unsupervised learning; wavelet transforms; SOM-wavelet networks method; biological model; face identification method; face image representation; face recognition; global information; self-organizing map; shape feature extraction; shape-based vector; unsupervised learning; Biological system modeling; Biology computing; Convergence; Data mining; Face recognition; Feature extraction; Neurons; Shape; Unsupervised learning; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Print_ISBN :
0-7803-9331-7
Type :
conf
DOI :
10.1109/ICME.2005.1521557
Filename :
1521557
Link To Document :
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