DocumentCode :
2957339
Title :
Face Recognition by LLE Dimensionality Reduction
Author :
Shenglin, Zhao ; Shan-an, Zhu
Author_Institution :
Zhejiang Univ., Hangzhou, China
Volume :
1
fYear :
2011
fDate :
28-29 March 2011
Firstpage :
121
Lastpage :
123
Abstract :
Nowadays we are surrounded by colorful images and image processing has become an important subject. We have to carry on all kinds of implementations such as image classification, image recognition, image searching and so on. However, direct operation to those images is difficult because of the features -- nonlinear, high dimensionality, large quantity. To reduce the dimensionality and remain original features, people created many algorithms such as PCA, MCS and ANN. In this paper, I introduce one dimensionality reduction called locally linear embedding (LLE), which is created by Sam and Lawrence. The LLE algorithm is one nonlinear dimensionality reduction method. I make use of the LLE algorithm to do an experiment of face recognition. By the LLE algorithm I reduce the 92*112-dimension-image to 6 dimensions and successful recognize the face image.
Keywords :
face recognition; image colour analysis; LLE dimensionality reduction; face recognition; image classification; image processing; image recognition; image searching; locally linear embedding; Cost function; Covariance matrix; Face recognition; Image recognition; Image reconstruction; Principal component analysis; Vectors; Dimensionality Reduction; Face Recognition; Image Processing; LLE;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location :
Shenzhen, Guangdong
Print_ISBN :
978-1-61284-289-9
Type :
conf
DOI :
10.1109/ICICTA.2011.37
Filename :
5750570
Link To Document :
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