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首页> 外文期刊>Computers & Graphics >Shape from sensors: Curve networks on surfaces from 3D orientations
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Shape from sensors: Curve networks on surfaces from 3D orientations

机译:传感器的形状:3D方向的曲面上的曲线网络

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摘要

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. (C) 2017 Elsevier Ltd. All rights reserved.
机译:我们提出了一种使用惯性传感器提供的方向来采集和重建3D曲线的新颖框架。虽然传感器形状重构的想法并不是什么新鲜事物,但我们提出了第一种方法,该方法仅使用方向和距离测量值以及一组用户定义的约束来创建具有单元复杂拓扑的连接良好的网络。通过直接使用方向,我们的方法可以有效解决由于数据不一致和传感器噪声而引起的问题。尽管最初是为重建物理形状而设计的,但该框架可用于直接在3D空间中“草图化”新形状。我们使用两种类型的采集设备来测试该方法的性能:标准智能手机和定制​​设备。 (C)2017 Elsevier Ltd.保留所有权利。

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