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AVSS
2006
IEEE
14 years 3 months ago
A Random Field Model for Improved Feature Extraction and Tracking
This paper presents a novel method for illuminationinvariant and contrast preserving feature extraction, aimed at improving performance of tracking under complex light condition. ...
Xiaotong Yuan, Stan Z. Li
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
14 years 2 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
CVPR
2012
IEEE
12 years 2 days ago
Beyond spatial pyramids: Receptive field learning for pooled image features
In this paper we examine the effect of receptive field designs on classification accuracy in the commonly adopted pipeline of image classification. While existing algorithms us...
Yangqing Jia, Chang Huang, Trevor Darrell
VVS
1998
IEEE
115views Visualization» more  VVS 1998»
14 years 1 months ago
Extracting ISO-Valued Features in 4-Dimensional Scalar Fields
Isosurfaces are an important tool for finding features in 3D scalar data. This paper describes how recursive contour meshing is applied to extract similar features in 4-dimensiona...
Chris Weigle, David C. Banks
AIPR
2004
IEEE
14 years 1 months ago
An Image Retrieval System Using Multispectral Random Field Models, Color, and Geometric Features
This paper describes a novel color texture-based image retrieval system for the query of an image database to find similar images to a target image. The retrieval process involves...
Orlando J. Hernandez, Alireza Khotanzad