Outlier detection and robust normal-curvature estimation in mobile laser scanning 3D point cloud data

Outlier detection and robust normal-curvature estimation in mobile laser scanning 3D point cloud data

This paper proposes two robust statistical techniques for outlier detection and robust saliency features, such as surface normal and curvature, estimation in laser scanning 3D point cloud data. One is based on a robust z-score and the other uses a Mahalanobis type robust distance. The methods couple...

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Bibliographic Details
Main Authors: Nurunnabi, A., West, Geoff, Belton, David
Format: Journal Article
Published: Elsevier BV 2015
Subjects:
Plane fitting
Surface reconstruction
Point cloud denoising
Segmentation
Robust saliency feature
Feature extraction
Online Access:http://hdl.handle.net/20.500.11937/15731

Internet

http://hdl.handle.net/20.500.11937/15731

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