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» Intrinsic Geometries in Learning
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PAMI
2006
141views more  PAMI 2006»
13 years 7 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee
ICPR
2010
IEEE
13 years 5 months ago
Discriminant and Invariant Color Model for Tracking under Abrupt Illumination Changes
The output from a color imaging sensor, or apparent color, can change considerably due to illumination conditions and scene geometry changes. In this work we take into account the...
Jorge Scandaliaris, Alberto Sanfeliu
ECCV
2006
Springer
14 years 9 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
ICPR
2008
IEEE
14 years 2 months ago
Convenient reconstruction of natural plants by images
Convenient reconstruction of natural plants is a difficult task because of their intrinsic complex geometry. In this paper, we propose a convenient image-based approach to modeli...
Wei Ma, Hongbin Zha
CGF
2002
127views more  CGF 2002»
13 years 7 months ago
Angle-Analyzer: A Triangle-Quad Mesh Codec
We present Angle-Analyzer, a new single-rate compression algorithm for triangle-quad hybrid meshes. Using a carefully-designed geometry-driven mesh traversal and an efficient enco...
Haeyoung Lee, Pierre Alliez, Mathieu Desbrun