کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6949065 1451231 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Refinement of LiDAR point clouds using a super voxel based approach
ترجمه فارسی عنوان
پاکسازی ابرهای لی دار با استفاده از رویکرد مبتنی بر سوکت وکسل
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
چکیده انگلیسی
We propose a new approach for automatic refinement of unorganized point clouds captured by LiDAR scanning systems. Given a point cloud, our method first abstracts the input data into super voxels via over segmentations, and then builds a K-nearest neighbor graph on these voxel nodes. ing into voxel representation provides a means to generate an elastic wireframe over the original data. An iterative resampling method is then introduced to project resampling points to all potential surfaces considering repulsion constraints from both interior and exterior of voxels. Our point consolidation process contributes to accurate normal estimation, uniform point distribution, and sufficient sampling density. Experiments and comparisons have demonstrated that the proposed method is effective on point clouds from a variety of datasets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 143, September 2018, Pages 213-221
نویسندگان
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