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» Tracking Large Variable Numbers of Objects in Clutter
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CVPR
2007
IEEE
14 years 9 months ago
Solving Large Scale Binary Quadratic Problems: Spectral Methods vs. Semidefinite Programming
In this paper we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of comput...
Carl Olsson, Anders P. Eriksson, Fredrik Kahl
DSMML
2004
Springer
14 years 1 months ago
Object Recognition via Local Patch Labelling
Abstract. In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of...
Christopher M. Bishop, Ilkay Ulusoy
CVPR
2004
IEEE
14 years 9 months ago
Point Matching as a Classification Problem for Fast and Robust Object Pose Estimation
We propose a novel approach to point matching under large viewpoint and illumination changes that is suitable for accurate object pose estimation at a much lower computational cos...
Vincent Lepetit, Julien Pilet, Pascal Fua
PAMI
2007
125views more  PAMI 2007»
13 years 7 months ago
Matching by Linear Programming and Successive Convexification
—We present a novel convex programming scheme to solve matching problems, focusing on the challenging problem of matching in a large search range and with cluttered background. M...
Hao Jiang, Mark S. Drew, Ze-Nian Li
BMCBI
2006
154views more  BMCBI 2006»
13 years 7 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...