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Research Article | Open Access

Fitting quadrics with a Bayesian prior

University of Bath, Claverton Down, Bath, BA2 7AY, UK.
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Abstract

Quadrics are a compact mathematical formulation for a range of primitive surfaces. A problem arises when there are not enough data points to compute the model but knowledge of the shape is available. This paper presents a method for fitting a quadric with a Bayesian prior. We use a matrix normal prior in order to favour ellipsoids when fitting to ambiguous data. The results show the algorithm copes well when there are few points in the point cloud, competing with contemporary techniques in the area.

Keywords

geometrystatisticsgraphicscomputer vision

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Computational Visual Media
Volume 2 Issue 2,
June 2016
Pages 107-117
DOI: 10.1007/s41095-016-0041-9

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Cite this article:
Beale D, Yang Y-L, Campbell N, et al. Fitting quadrics with a Bayesian prior. Computational Visual Media, 2016, 2(2): 107-117. https://doi.org/10.1007/s41095-016-0041-9

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Revised: 30 November 2015
Accepted: 13 January 2016
Published: 07 April 2016
© The Author(s) 2016

This article is published with open access at Springerlink.com

The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www. editorialmanager.com/cvmj.