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Superquadrics for segmentation and modeling range data

Aleš Leonardis and Aleš Jaklič and Franc Solina (1997) Superquadrics for segmentation and modeling range data. IEEE Transactions on Pattern Recognition and Machine Intelligence, 19 (11). pp. 1289-1295.

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    Abstract

    We present a novel approach to reliable and efficient recovery of part-descriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g., in terms of surfaces). The approach is based on the recover-andselect paradigm. We present several experiments on real and synthetic range images, where we demonstrate the stability of the results with respect to viewpoint and noise.

    Item Type: Article
    Keywords: range image segmentation, recover-and-select paradigm, recovery of volumetric models, superquadrics
    Language of Content: English
    Related URLs:
    URLURL Type
    http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(id=714324)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: 34
    Date Deposited: 22 Jan 2003
    Last Modified: 13 Dec 2013 07:55
    URI: http://eprints.fri.uni-lj.si/id/eprint/34

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