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» Application of Level Set Methods in Computer Vision
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CVPR
2012
IEEE
13 years 10 months ago
Robust camera self-calibration from monocular images of Manhattan worlds
We focus on the detection of orthogonal vanishing points using line segments extracted from a single view, and using these for camera self-calibration. Recent methods view this pr...
Horst Wildenauer, Allan Hanbury
CVPR
2012
IEEE
13 years 10 months ago
Depth from optical turbulence
Turbulence near hot surfaces such as desert terrains and roads during the summer, causes shimmering, distortion and blurring in images. While recent works have focused on image re...
Yuandong Tian, Srinivasa G. Narasimhan, Alan J. Va...
ICCV
2009
IEEE
17 years 16 days ago
Efficient Discriminative Learning of Parts-based Models
Supervised learning of a parts-based model can be for- mulated as an optimization problem with a large (exponen- tial in the number of parts) set of constraints. We show how thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
ICCV
2009
IEEE
1957views Computer Vision» more  ICCV 2009»
17 years 16 days ago
Robust Visual Tracking using L1 Minimization
In this paper we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, corru...
Xue Mei, Haibin Ling
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
17 years 16 days ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...