外核GPU加速了大型工业环境监测的表面重建

F. Mirallès, Chen Xu, D. Laurendeau
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引用次数: 0

摘要

提出了一种曲面重构算法的并行实现。该算法采用向量场表面表示,并在作者之前的工作中进行了改进,用于处理大规模环境重建。描述并比较了两种具有不同内存需求和处理速度的并行实现。与纯串行实现相比,这些并行实现将矢量场计算速度提高了31倍。该方法在Hydro-Quebec的不同数据集上进行了演示,使用了各种传感器:LiDAR、声纳和WireScan(我们实验室设计的水下激光扫描仪)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Out-of-core GPU accelerated surface reconstruction for large industrial environment monitoring
A parallel implementation of a surface reconstruction algorithm is presented. This algorithm uses the vector field surface representation and was adapted in a previous work by the authors to handle large scale environment reconstruction. Two parallel implementations with different memory requirements and processing speeds are described and compared. These parallel implementations increase the vector field computation speed by a factor of up to 31 times relative to a purely serial implementation. The method is demonstrated on different datasets captured on the sites of Hydro-Quebec using a variety of sensors: LiDAR, sonar and the WireScan, an underwater laser scanner designed at our laboratory.
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