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Shape from sensors: Curve networks on surfaces from 3D orientations
Tibor Stanko, Stefanie Hahmann, Georges-Pierre Bonneau, Nathalie Saguin-Sprynski

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

Science & Mathematics Published 2017 Verification Pending

Overview & Synopsis

We present a novel framework for acquisition and reconstruction of 3D curves using orientations provided by inertial 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 device.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Shape from sensors: Curve networks on surfaces from 3D orientations
Author / Organization Tibor Stanko, Stefanie Hahmann, Georges-Pierre Bonneau, Nathalie Saguin-Sprynski
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2017
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-204351
Original Source Link Visit Source Page on hal.science »