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» Structured Learning and Prediction in Computer Vision
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CVPR
2005
IEEE
14 years 10 months ago
A Caratheodory-Fejer Approach to Dynamic Appearance Modeling
This paper presents a technique to learn dynamic appearance models from a small number of training frames. Under this framework, dynamic appearance is modelled as an unknown opera...
Hwasup Lim, Octavia I. Camps, Mario Sznaier
ICPR
2004
IEEE
14 years 9 months ago
Tracking Periodic Motion using Bayesian Estimation
This paper presents a Bayesian approach to achieve efficient and accurate motion tracking in monocular image sequences. We first extract a deterministic motion model with six degr...
Andrew M. Wallace, Huiyu Zhou, Patrick R. Green
ICCV
2003
IEEE
14 years 10 months ago
Background Modeling and Subtraction of Dynamic Scenes
Background modeling and subtraction is a core component in motion analysis. The central idea behind such module is to create a probabilistic representation of the static scene tha...
Antoine Monnet, Anurag Mittal, Nikos Paragios, Vis...
DAGM
2011
Springer
12 years 8 months ago
Putting MAP Back on the Map
Conditional Random Fields (CRFs) are popular models in computer vision for solving labeling problems such as image denoising. This paper tackles the rarely addressed but important ...
Patrick Pletscher, Sebastian Nowozin, Pushmeet Koh...
ICCV
2007
IEEE
14 years 10 months ago
A Scene Representation Based on Multi-Modal 2D and 3D Features
Visually extracted 2D and 3D information have their own advantages and disadvantages that complement each other. Therefore, it is important to be able to switch between the differ...
Emre Baseski, Nicolas Pugeault, Sinan Kalkan, Dirk...