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ICIP
2006
IEEE
14 years 9 months ago
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Sheng-Yan Yang, Chiou-Ting Hsu
IJCV
2008
266views more  IJCV 2008»
13 years 7 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
IAJIT
2010
230views more  IAJIT 2010»
13 years 6 months ago
An Unsupervised Artificial Neural Network Method for Satellite Image Segmentation
: Image segmentation is an essential step in image processing. The goal of segmentation is to simplify and/or to change the representation of an image into a form easier to analyze...
Mohamad Awad
ECCV
2008
Springer
14 years 9 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...
ICCV
2009
IEEE
1136views Computer Vision» more  ICCV 2009»
15 years 14 days ago
Robust Graph-Cut Scene Segmentation and Reconstruction for Free-Viewpoint Video of Complex Dynamic Scenes
Current state-of-the-art image-based scene reconstruction techniques are capable of generating high-fidelity 3D models when used under controlled capture conditions. However, th...
Jean-Yves Guillemaut, Joe Kilner and Adrian Hilton