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» Diagonal principal component analysis for face recognition
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IJON
2007
166views more  IJON 2007»
13 years 10 months ago
Kernel PCA for similarity invariant shape recognition
We present in this paper a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the similarity (rotatio...
Hichem Sahbi
ICMCS
2000
IEEE
134views Multimedia» more  ICMCS 2000»
14 years 2 months ago
Information Access using Speech, Speaker and Face Recognition
We describe a scheme to combine the results of audio and face identification for multimedia indexing and retrieval. Audio analysis consists of speech and speaker recognition deri...
Mahesh Viswanathan, Homayoon S. M. Beigi, Alain Tr...
ECCV
2008
Springer
13 years 11 months ago
Discriminative Locality Alignment
—This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing...
Tianhao Zhang, Dacheng Tao, Jie Yang
ICIP
2002
IEEE
14 years 12 months ago
A kernel machine based approach for multi-view face recognition
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
Juwei Lu, Kostas N. Plataniotis, Anastasios N. Ven...
TNN
2008
128views more  TNN 2008»
13 years 10 months ago
Nonnegative Matrix Factorization in Polynomial Feature Space
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas