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WACV
2012
IEEE
12 years 3 months ago
Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures
A convenient way of analysing Riemannian manifolds is to embed them in Euclidean spaces, with the embedding typically obtained by flattening the manifold via tangent spaces. This...
Mehrtash Tafazzoli Harandi, Conrad Sanderson, Arno...
ICCV
2005
IEEE
14 years 1 months ago
Local Gabor Binary Pattern Histogram Sequence (LGBPHS): A Novel Non-Statistical Model for Face Representation and Recognition
For years, researchers in face recognition area have been representing and recognizing faces based on subspace discriminant analysis or statistical learning. Nevertheless, these a...
Wenchao Zhang, Shiguang Shan, Wen Gao, Xilin Chen,...
CVPR
2007
IEEE
14 years 9 months ago
Topology Preserving Log-Unbiased Nonlinear Image Registration: Theory and Implementation
In this paper, we present a novel framework for constructing large deformation log-unbiased image registration models that generate theoretically and intuitively correct deformati...
Igor Yanovsky, Paul M. Thompson, Stanley Osher, Al...
AINA
2009
IEEE
14 years 2 months ago
Quantitative Evaluation of Software Quality Metrics in Open-Source Projects
The validation of software quality metrics lacks statistical significance. One reason for this is that the data collection requires quite some effort. To help solve this problem,...
Henrike Barkmann, Rüdiger Lincke, Welf Lö...
SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
13 years 9 months ago
Distance Preserving Dimension Reduction for Manifold Learning
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Hyunsoo Kim, Haesun Park, Hongyuan Zha