Title
Face recognition by discriminant analysis with gabor tensor representation
Abstract
This paper proposes a novel face recognition method based on discriminant analysis with Gabor tensor representation. Although the Gabor face representation has achieved great success in face recognition, its huge number of features often brings about the problem of curse of dimensionality. In this paper, we propose a 3rd-order Gabor tensor representation derived from a complete response set of Gabor filters across pixel locations and filter types. 2D discriminant analysis is then applied to unfolded tensors to extract three discriminative subspaces. The dimension reduction is done in such a way that most useful information is retained. The subspaces are finally integrated for classification. Experimental results on FERET database show promising results of the proposed method.
Year
DOI
Venue
2007
10.1007/978-3-540-74549-5_10
ICB
Keywords
Field
DocType
gabor filter,feret database,novel face recognition method,face recognition,discriminant analysis,gabor face representation,gabor tensor representation,complete response,discriminative subspaces,dimension reduction,curse of dimensionality
Computer vision,Facial recognition system,Dimensionality reduction,Tensor,Pattern recognition,Computer science,Gabor wavelet,Curse of dimensionality,Artificial intelligence,Linear discriminant analysis,FERET database,Discriminative model
Conference
Volume
ISSN
ISBN
4642
0302-9743
3-540-74548-3
Citations 
PageRank 
References 
19
0.67
41
Authors
5
Name
Order
Citations
PageRank
Zhen Lei13613157.95
Rufeng Chu256027.44
Ran He31790108.39
Shengcai Liao4258298.34
Stan Z. Li58951535.26