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» Graph-Theoretical Methods in Computer Vision
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CVPR
2011
IEEE
15 years 2 months ago
Feature Guided Motion Artifact Reduction with Structure-Awareness in 4D CT Images
In this paper, we propose a novel method to reduce the magnitude of 4D CT artifacts by stitching two images with a data-driven regularization constrain, which helps preserve the l...
Dongfeng Han, John Bayouth, Qi Song, sudershan Bha...
VMV
2000
119views Visualization» more  VMV 2000»
15 years 8 months ago
Orientation Estimation Based on Weighted Projection onto Quadratic Polynomials
Essentially all Computer Vision strategies require initial computation of orientation structure or motion estimation. Although much work has been invested in this subfield, method...
Gunnar Farnebäck
CVPR
2010
IEEE
16 years 16 days ago
Weakly-Supervised Hashing in Kernel Space
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Yadong Mu, Jialie Shen, Shuicheng Yan
CVPR
2008
IEEE
16 years 9 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
ICPR
2002
IEEE
16 years 8 months ago
PCA in Autocorrelation Space
The use of higher order autocorrelations as features for pattern classification has been usually restricted to second or third orders due to high computational costs. Since the au...
Vlad Popovici, Jean-Philippe Thiran