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A Hyperquadric Model for {2-D} and {3-D} Data Fitting

Abstract : We present in this paper some improvements to the hyperquadric model allowing an efficient representation of the shape through a numerical parameterization and an energy minimization approach for data fitting. This last feature gives an accurate location of the image edge points independently of the implicit description of the shape. The advantage of our model is that it describes global shape properties through a unique implicit equation yielding a representation of the shape by means of its parameters, independently of the chosen numerical resolution
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https://hal.inria.fr/inria-00532676
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Submitted on : Thursday, November 4, 2010 - 1:37:28 PM
Last modification on : Friday, February 4, 2022 - 3:10:16 AM

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Isaac Cohen, L. Cohen. A Hyperquadric Model for {2-D} and {3-D} Data Fitting. Proceedings of the International Conference on Pattern Recognition, IEEE-IAPR, 1994, Jerusalem, Israel. ⟨10.1109/ICPR.1994.576961⟩. ⟨inria-00532676⟩

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