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ICCV
2009
IEEE
14 years 11 months ago
Decomposing a Scene into Geometric and Semantically Consistent Regions
High-level, or holistic, scene understanding involves reasoning about objects, regions, and the 3D relationships between them. This requires a representation above the level of ...
Stephen Gould, Richard Fulton, Daphne Koller
TSMC
2010
13 years 1 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer
VLSISP
2010
254views more  VLSISP 2010»
13 years 4 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 1 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
CVPR
2011
IEEE
12 years 10 months ago
Connecting Non-Quadratic Variational Models and MRFs
Spatially-discrete Markov random fields (MRFs) and spatially-continuous variational approaches are ubiquitous in low-level vision, including image restoration, segmentation, opti...
Kevin Schelten, Stefan Roth