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Abstract: This paper describes an estimation and representation method for object structure in 2D and 3D imagery. Local image features are modelled with Gaussian intensity profiles and estimated by a combination of a multiresolution, windowed Fourier approach followed by an iterative, minimum mean-square estimation. The method is computationally efficient and robust, giving accurate estimates of feature position, orientation and size. A structure classification and inference scheme is proposed, which... (Update)
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.... Feature Model If an ideal linear feature is windowed by a smooth function w( it can be regarded as a 2 dimensional Gaussian function [14], examples of which are shown in Figure 1. The 2 dimensional Gaussian function can be written in the form: G( x) 2 ) 1=2 jCj 1=2...
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BibTeX entry: (Update)
A. Bhalerao and R. Wilson, \Estimating local and global image structure using a gaussian intensity model," Medical Image Understanding and Analysis, 2001. http://citeseer.ist.psu.edu/bhalerao01estimating.html More
@misc{ bhalerao01estimating,
author = "A. Bhalerao and R. Wilson",
title = "Estimating local and global image structure using a gaussian intensity
model",
text = "A. Bhalerao and R. Wilson, \Estimating local and global image structure
using a gaussian intensity model, Medical Image Understanding and Analysis,
2001.",
year = "2001",
url = "citeseer.ist.psu.edu/bhalerao01estimating.html" }
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