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» Robust Image Registration using Mixtures of t-distributions
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CVPR
2007
IEEE
14 years 9 months ago
Robust Click-Point Linking: Matching Visually Dissimilar Local Regions
This paper presents robust click-point linking: a novel localized registration framework that allows users to interactively prescribe where the accuracy has to be high. By emphasi...
Kazunori Okada, Xiaolei Huang
ICRA
2008
IEEE
146views Robotics» more  ICRA 2008»
14 years 2 months ago
Visual servoing based on Gaussian mixture models
— In this paper we present a novel approach to robust visual servoing. This method removes the feature tracking step from a typical visual servoing algorithm. We do not need corr...
A. H. Abdul Hafez, Supreeth Achar, C. V. Jawahar
WBIR
2010
SPRINGER
14 years 22 days ago
Reliability-Driven, Spatially-Adaptive Regularization for Deformable Registration
We propose a reliability measure that identifies informative image cues useful for registration, and present a novel, data-driven approach to spatially adapt regularization to the...
Lisa Tang, Ghassan Hamarneh, Rafeef Abugharbieh
IPMI
2007
Springer
14 years 8 months ago
Learning Best Features and Deformation Statistics for Hierarchical Registration of MR Brain Images
A fully learning-based framework has been presented for deformable registration of MR brain images. In this framework, the entire brain is first adaptively partitioned into a numbe...
Guorong Wu, Feihu Qi, Dinggang Shen
IPMI
2001
Springer
14 years 8 months ago
Partial Volume Segmentation of Cerebral MRI Scans with Mixture Model Clustering
A mixture model clustering algorithm is presented for robust MRI brain image segmentation in the presence of partial volume averaging. The method uses additional classes to represe...
Aljaz Noe, James C. Gee