Diagnostics based Principal Component Analysis for Robust Plane Fitting in Laser Data

Diagnostics based Principal Component Analysis for Robust Plane Fitting in Laser Data

Plane fitting and obtaining characteristics (e.g., normal) from the estimated plane are fundamental tasks in many applications in which laser scanner 3D data is used. Unfortunately, laser data are not free from outliers. Principal Component Analysis (PCA) is a popular method for plane fitting, but i...

Full description

Bibliographic Details
Main Authors: Nurunnabi, Abdul, Belton, David, West, Geoff
Other Authors: N/A
Format: Conference Paper
Published: IEEE Inc. 2013
Subjects:
point cloud
surface reconstruction
robust normal
segmentation
Feature extraction
outlier
Online Access:http://hdl.handle.net/20.500.11937/8020

Internet

http://hdl.handle.net/20.500.11937/8020

Similar Items