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TSP
2008
178views more  TSP 2008»
13 years 4 months ago
Heteroscedastic Low-Rank Matrix Approximation by the Wiberg Algorithm
Abstract--Low-rank matrix approximation has applications in many fields, such as 2D filter design and 3D reconstruction from an image sequence. In this paper, one issue with low-ra...
Pei Chen
COMPGEOM
2008
ACM
13 years 6 months ago
Towards persistence-based reconstruction in euclidean spaces
Manifold reconstruction has been extensively studied for the last decade or so, especially in two and three dimensions. Recent advances in higher dimensions have led to new method...
Frédéric Chazal, Steve Oudot
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
13 years 11 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
ICCV
2001
IEEE
14 years 6 months ago
A Versatile Method for Trifocal Tensor Estimation
Reliable estimation of the trifocal tensor is crucial for 3D reconstruction from uncalibrated cameras. The estimation process is based on minimizing the geometric distances betwee...
Bogdan Matei, Bogdan Georgescu, Peter Meer