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» Discrete optimization in computer vision
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ICPR
2000
IEEE
16 years 5 months ago
Reduction of Bias in Maximum Likelihood Ellipse Fitting
An improved maximum likelihood estimator for ellipse fitting based on the heteroscedastic errors-in-variables (HEIV) regression algorithm is proposed. The technique significantly ...
Bogdan Matei, Peter Meer
ACCV
2009
Springer
15 years 11 months ago
Planar Scene Modeling from Quasiconvex Subproblems
In this paper, we propose a convex optimization based approach for piecewise planar reconstruction. We show that the task of reconstructing a piecewise planar environment can be se...
Visesh Chari, Anil Kumar Nelakanti, Chetan Jakkoju...
IPPS
2000
IEEE
15 years 8 months ago
Dynamic Data Layouts for Cache-Conscious Factorization of DFT
Effective utilization of cache memories is a key factor in achieving high performance in computing the Discrete Fourier Transform (DFT). Most optimizationtechniques for computing ...
Neungsoo Park, Dongsoo Kang, Kiran Bondalapati, Vi...
FGR
2006
IEEE
163views Biometrics» more  FGR 2006»
15 years 10 months ago
Human Action Recognition Using Multi-View Image Sequences Features
Recognizing human action from image sequences is an active area of research in computer vision. In this paper, we present a novel method for human action recognition from image se...
Mohiuddin Ahmad, Seong-Whan Lee
SCALESPACE
2005
Springer
15 years 9 months ago
Relations Between Higher Order TV Regularization and Support Vector Regression
We study the connection between higher order total variation (TV) regularization and support vector regression (SVR) with spline kernels in a one-dimensional discrete setting. We p...
Gabriele Steidl, Stephan Didas, Julia Neumann