Matching Point Clouds with STL Models by Using the Principle Component Analysis and a Decomposition into Geometric Primitives
While repairing industrial machines or vehicles, recognition of components is a critical and time-consuming task for a human. In this paper, we propose to automatize this task. We start with a Principal Component Analysis (PCA), which fits the scanned point cloud with an ellipsoid by computing the e...
Main Authors: | Erika Straková, Dalibor Lukáš, Zdenko Bobovský, Tomáš Kot, Milan Mihola, Petr Novák |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-03-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/5/2268 |
Similar Items
-
Using Virtual Scanning to Find Optimal Configuration of a 3D Scanner Turntable for Scanning of Mechanical Parts
by: Tomáš Kot, et al.
Published: (2021-08-01) -
Geometric Primitives in LiDAR Point Clouds: A Review
by: Shaobo Xia, et al.
Published: (2020-01-01) -
The synthesis of a segmented stair-climbing wheel
by: Vladimir Mostyn, et al.
Published: (2018-01-01) -
Out of Plumb Assessment for Cylindrical-Like Minaret Structures Using Geometric Primitives Fitting
by: Bashar Alsadik, et al.
Published: (2019-01-01) -
Multiple STL decomposition in discovering a multi-seasonality of intraday trading volume
by: Josip Arnerić
Published: (2021-01-01)