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Conic Fitting Using the Geometric Distance

Peter Sturm 1 Pau Gargallo 1 
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : We consider the problem of fitting a conic to a set of 2D points. It is commonly agreed that minimizing geometrical error, i.e. the sum of squared distances between the points and the conic, is better than using an algebraic error measure. However, most existing methods rely on algebraic error measures. This is usually motivated by the fact that point-to-conic distances are difficult to compute and the belief that non-linear optimization of conics is computationally very expensive. In this paper, we describe a parameterization for the conic fitting problem that allows to circumvent the difficulty of computing point-to-conic distances, and we show how to perform the non-linear optimization process efficiently.
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Submitted on : Thursday, May 14, 2009 - 4:59:38 PM
Last modification on : Thursday, January 20, 2022 - 5:30:20 PM
Long-term archiving on: : Thursday, June 10, 2010 - 9:24:22 PM


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Peter Sturm, Pau Gargallo. Conic Fitting Using the Geometric Distance. ACCV 2007 - 8th Asian Conference on Computer Vision, Nov 2007, Tokyo, Japan. pp.784-795, ⟨10.1007/978-3-540-76390-1_77⟩. ⟨inria-00384284⟩



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