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» Local Dimensionality Reduction
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114
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ICASSP
2011
IEEE
14 years 7 months ago
Eigenspace sparsity for compression and denoising
Sparsity in the eigenspace of signal covariance matrices is exploited in this paper for compression and denoising. Dimensionality reduction (DR) and quantization modules present i...
Ioannis D. Schizas, Georgios B. Giannakis
JMLR
2012
13 years 5 months ago
Sparse Higher-Order Principal Components Analysis
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Genevera Allen
CRV
2006
IEEE
176views Robotics» more  CRV 2006»
15 years 5 months ago
Stereo Retinex
The retinex algorithm for lightness and color constancy is extended to include 3-dimensional spatial information reconstructed from a stereo image. A key aspect of traditional ret...
Weihua Xiong, Brian V. Funt
CGF
2010
144views more  CGF 2010»
15 years 3 months ago
Dynamic Multi-View Exploration of Shape Spaces
Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model mod...
Stef Busking, Charl P. Botha, Frits H. Post
123
Voted
IJCV
2007
135views more  IJCV 2007»
15 years 3 months ago
Application of the Fisher-Rao Metric to Ellipse Detection
The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold corresponds to an ellipse in the image. The parame...
Stephen J. Maybank