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Abstract: In this paper we describe a statistical method for the integration of an unlimited number of cues within a deformable model framework. We treat each cue as a random variable, each of which is the sum of a large number of local contributions with unknown probability distribution functions. Under the assumption that these distributions are independent, the overall distributions of the generalized cue forces can be approximated with multidimensional Gaussians, as per the central limit theorem.... (Update)
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.... Since then it has been used in numerical applications [31] electrical engineering [16] computer graphics [13] and computer vision [21]. Gaussian probability distributions are a widely used tool in engineering [17] as they have several desirable properties: preservation...
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BibTeX entry: (Update)
@misc{ goldenstein-affine,
author = "Siome Goldenstein and Christian Vogler and Dimitris Metaxas",
title = "Affine arithmetic based estimation of cue distributions in deformable model
tracking",
url = "citeseer.nj.nec.com/goldenstein01affine.html" }
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10 Optical flow constraints on deformable models with applicati.. - de Carlo, Metaxas - 2000
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