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ICCV
2005
IEEE
14 years 7 months ago
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization
We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the pas...
Tamir Hazan, Simon Polak, Amnon Shashua
CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 5 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
ICIP
2009
IEEE
14 years 6 months ago
Facial Expression Recognition Based On Graph-preserving Sparse Non-negative Matrix Factorization
In this paper, we present a novel algorithm for representing facial expressions. The algorithm is based on the non-negative matrix factorization (NMF) algorithm, which decomposes ...
ICCV
2005
IEEE
14 years 7 months ago
Learning Non-Negative Sparse Image Codes by Convex Programming
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Christoph Schnörr, Matthias Heiler
TIP
2010
154views more  TIP 2010»
13 years 3 months ago
Projective Nonnegative Graph Embedding
—We present in this paper a general formulation for nonnegative data factorization, called projective nonnegative graph embedding (PNGE), which 1) explicitly decomposes the data ...
Xiaobai Liu, Shuicheng Yan, Hai Jin