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

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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...

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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

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