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ECCV
2008
Springer
14 years 10 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
ICML
2010
IEEE
13 years 9 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
TSP
2010
13 years 3 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
ICANN
2003
Springer
14 years 1 months ago
Sparse Coding with Invariance Constraints
We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set...
Heiko Wersing, Julian Eggert, Edgar Körner
PG
2002
IEEE
14 years 1 months ago
The Light Field Oracle
We present the light field oracle, a novel mathematical concept for the acquisition, processing and representation of light fields. We first compute a hierarchical representati...
Reto Lütolf, Bernt Schiele, Markus H. Gross