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CVPR
2008
IEEE
14 years 9 months ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
CVPR
2008
IEEE
14 years 9 months ago
Articulated shape matching using Laplacian eigenfunctions and unsupervised point registration
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to...
Diana Mateus, Radu Horaud, David Knossow, Fabio Cu...
ICCV
2007
IEEE
14 years 9 months ago
Object Localisation Using Generative Probability Model for Spatial Constellation and Local Image Features
In this paper we apply state-of-the-art approach to object detection and localisation by incorporating local descriptors and their spatial configuration into a generative probabil...
Joni-Kristian Kamarainen, Miroslav Hamouz, Josef K...
ECCV
2008
Springer
14 years 9 months ago
SIFT Flow: Dense Correspondence across Different Scenes
While image registration has been studied in different areas of computer vision, aligning images depicting different scenes remains a challenging problem, closer to recognition tha...
Ce Liu, Jenny Yuen, Antonio B. Torralba, Josef Siv...
ECCV
2006
Springer
14 years 9 months ago
A General Framework for Motion Segmentation: Independent, Articulated, Rigid, Non-rigid, Degenerate and Non-degenerate
Abstract. We cast the problem of motion segmentation of feature trajectories as linear manifold finding problems and propose a general framework for motion segmentation under affin...
Jingyu Yan, Marc Pollefeys