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CVPR
2004
IEEE
16 years 9 months ago
Motion-Based Background Subtraction Using Adaptive Kernel Density Estimation
Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that consist of static or quasi-static structures. When...
Anurag Mittal, Nikos Paragios
CVPR
2005
IEEE
16 years 9 months ago
A Cross-Validatory Statistical Approach to Scale Selection for Image Denoising by Nonlinear Diffusion
Scale-spaces induced by diffusion processes play an important role in many computer vision tasks. Automatically selecting the most appropriate scale for a particular problem is a ...
George Papandreou, Petros Maragos
ICCV
2007
IEEE
16 years 9 months ago
LogCut - Efficient Graph Cut Optimization for Markov Random Fields
Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...
Victor S. Lempitsky, Carsten Rother, Andrew Blake
ICCV
2005
IEEE
16 years 9 months ago
Learning Non-Negative Sparse Image Codes by Convex Programming
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Christoph Schnörr, Matthias Heiler
ECCV
2008
Springer
16 years 9 months ago
Surface Visibility Probabilities in 3D Cluttered Scenes
Many methods for 3D reconstruction in computer vision rely on probability models, for example, Bayesian reasoning. Here we introduce a probability model of surface visibilities in ...
Michael S. Langer