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ICCV
2005
IEEE
15 years 11 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
80
Voted
CORR
2004
Springer
152views Education» more  CORR 2004»
14 years 9 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
15 years 10 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
15 years 11 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»
14 years 7 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