Fitting quadrics with a Bayesian prior


Beale, D., Yang, Y., Campbell, N., Cosker, D. and Hall, P., 2016. Fitting quadrics with a Bayesian prior. Computational Visual Media, 2 (2), pp. 107-117.

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    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 on ambiguous data. The results show the algorithm to cope well when there are few points in the point cloud, competing with contemporary techniques in the area.


    Item Type Articles
    CreatorsBeale, D., Yang, Y., Campbell, N., Cosker, D. and Hall, P.
    Related URLs
    URLURL Type Full-text
    Uncontrolled Keywordsgeometry, statistics, graphics, computer vision
    DepartmentsFaculty of Science > Computer Science
    Research CentresMedia Technology Research Centre
    EPSRC Centre for Doctoral Training in Statistical Mathematics (SAMBa)
    Publisher Statementcvmpaper.pdf: The final publication is available at Springer via
    ID Code49936


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