Shape from sensors: curve networks on surfaces from 3D orientations - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Computers and Graphics Année : 2017

Shape from sensors: curve networks on surfaces from 3D orientations

Résumé

We present a novel framework for acquisition and reconstruction of 3D curves using orientations provided by iner-tial sensors. While the idea of sensor shape reconstruction is not new, we present the first method for creating well-connected networks with cell complex topology using only orientation and distance measurements and a set of user-defined constraints. By working directly with orientations, our method robustly resolves problems arising from data inconsistency and sensor noise. Although originally designed for reconstruction of physical shapes, the framework can be used for "sketching" new shapes directly in 3D space. We test the performance of the method using two types of acquisition devices: a standard smartphone, and a custom-made prototype called the Morphorider.
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Dates et versions

hal-01524740 , version 1 (18-05-2017)
hal-01524740 , version 2 (19-05-2017)

Identifiants

  • HAL Id : hal-01524740 , version 1

Citer

Tibor Stanko, Stefanie Hahmann, Georges-Pierre Bonneau, Nathalie Saguin-Sprynski. Shape from sensors: curve networks on surfaces from 3D orientations. Computers and Graphics, 2017. ⟨hal-01524740v1⟩
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