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» Modeling Image Textures by Gibbs Random Fields
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ICPR
2006
IEEE
15 years 11 months ago
Illumination Invariant Texture Retrieval
Two fast illumination invariant image retrieval methods for scenes comprising textured objects with variable illumination are introduced. Both methods are based on texture gradien...
Michal Haindl, Pavel Vacha
76
Voted
ICPR
2002
IEEE
15 years 11 months ago
Illumination Invariant Segmentation of Spatio-Temporal Images by Spatio-Temporal Markov Random Field Model
For many years, object tracking in images has suffered from the problems of occlusions and illumination effects. In order to resolve occlusion problems, we have been proposing the...
Shunsuke Kamijo, Katsushi Ikeuchi, Masao Sakauchi
CVPR
2001
IEEE
16 years 5 days ago
Texture Replacement in Real Images
Texture replacement in real images has many applications, such as interior design, digital movie making and computer graphics. The goal is to replace some specified texture patter...
Yanghai Tsin, Yanxi Liu, Visvanathan Ramesh
VDB
1998
117views Database» more  VDB 1998»
14 years 11 months ago
Textural Features and Relevance Feedback for Image Retrieval
This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentati...
Eugenio Di Sciascio, Giacomo Piscitelli, Augusto C...
AUTOMATICA
2006
122views more  AUTOMATICA 2006»
14 years 10 months ago
Gibbs sampler-based coordination of autonomous swarms
In this paper a novel, Gibbs sampler-based algorithm is proposed for coordination of autonomous swarms. The swarm is modeled as a Markov random field (MRF) on a graph with a time-...
Wei Xi, Xiaobo Tan, John S. Baras