计算机工程与应用2018，Vol.54Issue(1)：191-195,203,6.DOI:10.3778/j.issn.1002-8331.1607-0229
基于OpenCL的点云分割方法
Method of point cloud segmentation based on OpenCL
摘要
Abstract
The segmentation of point cloud is one of the key technologies of reverse engineering reconstruction, however, the computation time of point cloud feature is heavy. So it is of significance to accelerate the algorithm by heterogeneous computing with OpenCL. This paper aims to segment unordered point cloud efficiently with OpenCL. The algorithm is mainly divided into three steps:compute parallel eigenvalues of point cloud data, compute parallel normal, and curvature computation of point cloud. In the process of calculation, the data storage structure, the efficiency of data access, and the complexity of the algorithm have been optimized and improved according to the GPU parallel architecture and hardware features. Experimental results show that the algorithm takes full advantage of the parallel processing capabilities of OpenCL, the running time is 16 times faster than implementation of the CPU.关键词
OpenCL/图形处理器(GPU)/点云分割Key words
OpenCL/Graphics Processing Unit(GPU)/point cloud segmentation分类
信息技术与安全科学引用本文复制引用
范昱伶,王美丽,何东健..基于OpenCL的点云分割方法[J].计算机工程与应用,2018,54(1):191-195,203,6.基金项目
国家高技术研究发展计划(863)(No.2013AA102304) （863）
国家自然科学基金(No.61402374) （No.61402374）
第56批中国博士后科学基金(No.2014M562457). （No.2014M562457）
