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SIGGRAPH

2010

ACM

2010

ACM

We propose a technique that takes a triangulated surface as input and outputs a surface with the same topology but altered geometry such that each polygon falls into a set of discrete equivalence classes. We begin by describing an error function that measures how close the polygons are to satisfying this criteria. To optimize this error function, we ﬁrst cluster triangles into discrete sets such that the assignment of sets minimizes our error. We then ﬁnd canonical polygons for each set using nonlinear optimization. Next, we solve a Poisson equation to ﬁnd positions of vertices such that the surface polygons match the canonical polygons as close as possible. We also describe how to incorporate a fairness criteria into the optimization to avoid oscillations of the surface. We iterate this entire process until we reach a user speciﬁed tolerance, possibly adding clusters during iteration to guarantee convergence. We have been able to successfully reduce the number of unique trian...

Added |
28 Jul 2010 |

Updated |
29 Jul 2010 |

Type |
Conference |

Year |
2010 |

Where |
SIGGRAPH |

Authors |
Mayank Singh, Scott Schaefer |

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