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» On Estimation of Fundamental Matrix in Computational Stereo
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CORR
2008
Springer
143views Education» more  CORR 2008»
13 years 7 months ago
Locally computable approximations for spectral clustering and absorption times of random walks
We address the problem of determining a natural local neighbourhood or "cluster" associated to a given seed vertex in an undirected graph. We formulate the task in terms...
Pekka Orponen, Satu Elisa Schaeffer, Vanesa Avalos...
IJCV
2006
261views more  IJCV 2006»
13 years 7 months ago
Non-Rigid Stereo Factorization
In this paper we address the problem of recovering 3D non-rigid structure from a sequence of images taken with a stereo pair. We have extended existing non-rigid factorization algo...
Alessio Del Bue, Lourdes de Agapito
IJCV
2000
133views more  IJCV 2000»
13 years 7 months ago
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
Yoram Leedan, Peter Meer

Book
5396views
15 years 6 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
14 years 2 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