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» Covariant Derivatives and Vision
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ICCV
2005
IEEE
14 years 10 months ago
Modeling Scenes with Local Descriptors and Latent Aspects
We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
ICCV
2003
IEEE
14 years 10 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...
ECCV
2008
Springer
14 years 10 months ago
Segmentation and Recognition Using Structure from Motion Point Clouds
We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3...
Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur...
ECCV
2008
Springer
14 years 10 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
ECCV
2004
Springer
14 years 10 months ago
Interactive Image Segmentation Using an Adaptive GMMRF Model
The problem of interactive foreground/background segmentation in still images is of great practical importance in image editing. The state of the art in interactive segmentation is...
Andrew Blake, Carsten Rother, M. Brown, Patrick P&...