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» Modeling non-gaussian noise for robust image analysis
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ICPR
2002
IEEE
14 years 8 months ago
Robust Appearance-Based Object Recognition Using a Fully Connected Markov Random Field
This paper presents a new kernel method for appearance-based object recognition, highly robust to noise and occlusion. It consists of a fully connected Markov Random Field that in...
Barbara Caputo, Sahla Bouattour, Heinrich Niemann
ICCV
2001
IEEE
14 years 9 months ago
Robust Histogram Construction from Color Invariants
An effective object recognition scheme is to represent and match images on the basis of histograms derived from photometric color invariants. A drawback, however, is that certain c...
Theo Gevers
VIS
2008
IEEE
162views Visualization» more  VIS 2008»
14 years 9 months ago
Geodesic Distance-weighted Shape Vector Image Diffusion
Abstract--This paper presents a novel and efficient surface matching and visualization framework through the geodesic distanceweighted shape vector image diffusion. Based on confor...
Jing Hua, Zhaoqiang Lai, Ming Dong, Xianfeng Gu...
CVPR
2007
IEEE
14 years 9 months ago
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
SMA
2008
ACM
396views Solid Modeling» more  SMA 2008»
13 years 7 months ago
Fast mesh segmentation using random walks
3D mesh models are now widely available for use in various applications. The demand for automatic model analysis and understanding is ever increasing. Mesh segmentation is an impo...
Yu-Kun Lai, Shi-Min Hu, Ralph R. Martin, Paul L. R...