Comparative Study of the Representative Algorithms for Fitting Spherical Target Based on Point Cloud
Author:
Affiliation:
1. School of Geomatics Science and Technology, Nanjing Tech University, Nanjing, China
2. Jiangsu Hydraulic Research Institute, Nanjing, China
Funder
Project of Hydraulic Science and Technology of Jiangsu Province
Research Project of Jiangsu Hydraulic Research Institute
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09969628.pdf?arnumber=9969628
Reference60 articles.
1. Mature pomegranate fruit detection and location combining improved F-PointNet with 3D point cloud clustering in orchard
2. An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
3. Extraction of indoor objects based on the exponential function density clustering model
4. Improved RANSAC Point Cloud Spherical Target Detection and Parameter Estimation Method Based on Principal Curvature Constraint
5. A new high-precision sphere-fitting method with small segment angles
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