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2D shape deformation using nonlinear least squares optimization

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Abstract

This paper presents a novel 2D shape deformation algorithm based on nonlinear least squares optimization. The algorithm aims to preserve two local shape properties: the Laplacian coordinates of the boundary curve and the local area of the shape interior, which are together represented in a non-quadratic energy function. An iterative Gauss–Newton method is used to minimize this nonlinear energy function. The result is an interactive shape deformation system that can achieve physically plausible results that are difficult to achieve with previous linear least squares methods. In addition to this algorithm that preserves local shape properties, we also introduce a scheme to preserve the global area of the shape, which is useful for deforming incompressible objects.

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Authors and Affiliations

  1. Microsoft Research Asia, Beijing, China

    Weiwei Xu, Kun Zhou & Baining Guo

  2. University of Wisconsin, Milwaukee, WI, USA

    Yanlin Weng

  3. Zhejiang University, Hangzhou, Zhejiang, P.R. China

    Yanchen Wu

Authors
  1. Yanlin Weng
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  2. Weiwei Xu
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  3. Yanchen Wu
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  4. Kun Zhou
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  5. Baining Guo
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Correspondence to Kun Zhou.

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Weng, Y., Xu, W., Wu, Y. et al. 2D shape deformation using nonlinear least squares optimization . Visual Comput 22, 653–660 (2006). https://doi.org/10.1007/s00371-006-0054-y

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  • DOI: https://doi.org/10.1007/s00371-006-0054-y

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