NDLI: Diagnostics based principal component analysis for robust plane fitting in laser data

Content Provider	IEEE Xplore Digital Library
Author	Nurunnabi, A. Belton, D. West, G.
Copyright Year	2014
Description	Author affiliation: Dept. of Spatial Sci., Curtin Univ., Perth, WA, Australia (Nurunnabi, A.; Belton, D.; West, G.)
Abstract	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 it is known that PCA is very sensitive to outliers and gives misleading non-robust results. We present a robust plane fitting algorithm based on PCA coupled with an outlier detecting diagnostic statistical approach. In this method, the recently introduced robust scatter matrix is used to calculate robust statistical distance for finding outliers. After excluding outliers, PCA is performed on the outlier free data which is used for fitting planar surfaces and to estimate robust normal and other parameters. Demonstration of the new algorithm through several synthetic and vehicle based laser scanning data show that the proposed method is efficient, and gives robust estimates. Results outperform Least Squares (LS), PCA and are significantly better than the well-known RANSAC in terms of time, accuracy and robustness. This method has great potential for robust segmentation, surface reconstruction, and other point cloud processing tasks.
Starting Page	484
Ending Page	489
File Size	743739
Page Count	6
File Format	PDF
e-ISBN	9781479934973
DOI	10.1109/ICCITechn.2014.6997319
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-08
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Fitting robust normal outlier surface reconstruction point cloud Surface reconstruction Three-dimensional displays Feature extraction segmentation Robustness Surface fitting Principal component analysis
Content Type	Text
Resource Type	Article

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