کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
555007 1451261 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications
ترجمه فارسی عنوان
تقسیم بندی مبتنی بر Octree برای داده های Cloud Cloud LiDAR در برنامه های کاربردی صنعتی
کلمات کلیدی
لیدار زمینی؛ نقطه تقسیم بندی ابر؛ تقسیم و ادغام؛ سیستم های لوله کشی؛ تشخیص سیلندر
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
چکیده انگلیسی

Automated and efficient algorithms to perform segmentation of terrestrial LiDAR data is critical for exploitation of 3D point clouds, where the ultimate goal is CAD modeling of the segmented data. In this work, a novel segmentation technique is proposed, starting with octree decomposition to recursively divide the scene into octants or voxels, followed by a novel split and merge framework that uses graph theory and a series of connectivity analyses to intelligently merge components into larger connected components. The connectivity analysis, based on a combination of proximity, orientation, and curvature connectivity criteria, is designed for the segmentation of pipes, vessels, and walls from terrestrial LiDAR data of piping systems at industrial sites, such as oil refineries, chemical plants, and steel mills. The proposed segmentation method is exercised on two terrestrial LiDAR datasets of a steel mill and a chemical plant, demonstrating its ability to correctly reassemble and segregate features of interest.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 113, March 2016, Pages 59–74
نویسندگان
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