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» Computing the Dimension of Linear Subspaces
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110
Voted
CEC
2005
IEEE
15 years 5 months ago
Nonlinear mapping using particle swarm optimisation
Abstract— Nonlinear mapping is an approach of multidimensional scaling where a high-dimensional space is transformed into a lower-dimensional space such that the topological char...
Auralia I. Edwards, Andries Petrus Engelbrecht, Ne...
152
Voted
CVPR
1998
IEEE
16 years 5 months ago
Motion Feature Detection Using Steerable Flow Fields
The estimation and detection of occlusion boundaries and moving bars are important and challenging problems in image sequence analysis. Here, we model such motion features as line...
David J. Fleet, Michael J. Black, Allan D. Jepson
108
Voted
ICPR
2008
IEEE
15 years 10 months ago
Optimal feature weighting for the discrete HMM
We propose a modified discrete HMM that includes a feature weighting discrimination component. We assume that the feature space is partitioned into subspaces and that the relevan...
Oualid Missaoui, Hichem Frigui
110
Voted
CVPR
2007
IEEE
16 years 5 months ago
Linear Laplacian Discrimination for Feature Extraction
Discriminant feature extraction plays a fundamental role in pattern recognition. In this paper, we propose the Linear Laplacian Discrimination (LLD) algorithm for discriminant fea...
Deli Zhao, Zhouchen Lin, Rong Xiao, Xiaoou Tang
127
Voted
CVPR
2009
IEEE
1133views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Sparse Subspace Clustering
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine subspaces embedded in a high-dimensional space. Our ...
Ehsan Elhamifar, René Vidal