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» Physically Based Methods for Tensor Field Visualization
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ICCV
2007
IEEE
15 years 11 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
APVIS
2009
14 years 10 months ago
Visualizing diffusion tensor imaging data with merging ellipsoids
Diffusion tensor fields reveal the underlying anatomical structures in biological tissues such as neural fibers in the brain. Most current methods for visualizing the diffusion te...
Wei Chen, Song Zhang, Stephen Correia, David F. Ta...
ICCV
2011
IEEE
13 years 9 months ago
A Nonparametric Riemannian Framework on Tensor Field with Application to Foreground Segmentation
Background modelling on tensor field has recently been proposed for foreground detection tasks. Taking into account the Riemannian structure of the tensor manifold, recent resear...
Rui Caseiro, João F. Henriques, Pedro Martins, Jo...
DSSCV
2005
Springer
15 years 3 months ago
From Stochastic Completion Fields to Tensor Voting
Abstract. Several image processing algorithms imitate the lateral interaction of neurons in the visual striate cortex V1 to account for the correlations along contours and lines. H...
Markus van Almsick, Remco Duits, Erik Franken, Bar...
83
Voted
MICCAI
2003
Springer
15 years 10 months ago
Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach
Abstract. In this paper we propose a novel non-Gaussian MRF for regularization of tensor fields for fiber tract enhancement. Two entities are considered in the model, namely, the l...
Marcos Martín-Fernández, Carlos Albe...