4.7 Article

Optimizing Global Injectivity for Constrained Parameterization

期刊

ACM TRANSACTIONS ON GRAPHICS
卷 40, 期 6, 页码 -

出版社

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3478513.3480556

关键词

Parameterization; mapping; bijective

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Existing algorithms for obtaining injective parameterizations of triangulated meshes are limited by either requiring initialization from an injective starting state or only preventing triangle inversion, which is insufficient to ensure injectivity. The presented algorithm introduces a new energy, smooth excess area (SEA), to measure non-injectivity in a map and successfully recovers globally injective maps for a high percentage of benchmarks. The analysis shows that maps minimizing SEA are guaranteed to be locally injective and almost globally injective, making it a promising method for injective mapping.
Injective parameterizations of triangulated meshes are critical across applications but remain challenging to compute. Existing algorithms to find injectivity either require initialization from an injective starting state, which is currently only possible without positional constraints, or else can only prevent triangle inversion, which is insufficient to ensure injectivity. Here we present, to our knowledge, the first algorithm for recovering a globally injective parameterization from an arbitrary non-injective initial mesh subject to stationary constraints. These initial meshes can be inverted, wound about interior vertices and/or overlapping. Our algorithm in turn enables globally injective mapping for meshes with arbitrary positional constraints. Our key contribution is a new energy, called smooth excess area (SEA), that measures non-injectivity in a map. This energy is well-defined across both injective and non-injective maps and is smooth almost everywhere, making it readily minimizable using standard gradient-based solvers starting from a non-injective initial state. Importantly, we show that maps minimizing SEA are guaranteed to be locally injective and almost globally injective, in the sense that the overlapping area can be made arbitrarily small. Analyzing SEA's behavior over a new benchmark set designed to test injective mapping, we find that optimizing SEA successfully recovers globally injective maps for 85% of the benchmark and obtains locally injective maps for 90%. In contrast, state-of-the-art methods for removing triangle inversion obtain locally injective maps for less than 6% of the benchmark, and achieve global injectivity (largely by chance as prior methods are not designed to recover it) on less than 4%.

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