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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)
Context of citations to this paper: More
.... 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)
S. Goldenstein, C. Vogler, and D. Metaxas. Affine arithmetic based estimation of cue distributions in deformable model tracking. In Proceedings of CVPR, pages 1098--1105, 2001. http://citeseer.ist.psu.edu/goldenstein01affine.html More
@misc{ goldenstein01affine,
author = "S. Goldenstein and C. Vogler and D. Metaxas",
title = "Affine arithmetic based estimation of cue distributions in deformable model
tracking",
text = "S. Goldenstein, C. Vogler, and D. Metaxas. Affine arithmetic based estimation
of cue distributions in deformable model tracking. In Proceedings of CVPR,
pages 1098--1105, 2001.",
year = "2001",
url = "citeseer.ist.psu.edu/goldenstein01affine.html" }
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