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Moments of Superellipsoids and their Application to Range Image Registration

Aleš Jaklič and Franc Solina (2003) Moments of Superellipsoids and their Application to Range Image Registration.

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    Abstract— Cartesian moments are frequently used global geometrical features in computer vision for object pose estimation and recognition. In the paper we derive a closed form expression for 3D Cartesian moment of order p+q+r of a superellipsoid in its canonical coordinate system. We also show how 3D Cartesian moment of a globally deformed superellipsoid in general position and orientation can be computed as a linear combination of 3D Cartesian moments of the corresponding non-deformed superellipsoid in canonical coordinate system. Additionally, moments of objects that are compositions of superellipsoids can be computed as simple sums of moments of individual parts. To demonstrate practical application of the derived results we register pairs of range images based on moments of recovered compositions of superellipsoids. We use a standard technique to find centers of gravity and principal axes in pairs of range images while third-order moments are used to resolve the fourway ambiguity. Experimental results show expected improvement of recovered rigid transformation based on moments of recovered superellipsoids as compared to the registration based on moments of raw range image data. Beside object pose estimation the presented results can be directly used for object recognition with moments and/or moment invariants as object features.

    Item Type: Article
    Additional Information: To appear the Special issue on 3D Image Analysis and Modelling IEEE SMC--PART B: CYBERNETICS, 2003
    Keywords: 3D Cartesian moments, superellipse, superellipsoid, transformations of 3D moments, registration
    Language of Content: English
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    http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(id=3763284)Alternative location
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Divisions: Faculty of Computer and Information Science > Computer Vision Laboratory
    Item ID: 35
    Date Deposited: 10 Feb 2003
    Last Modified: 11 Dec 2013 11:28
    URI: http://eprints.fri.uni-lj.si/id/eprint/35

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