A FRAMEWORK FOR POSITION UNCERTAINTY OF UNORGANISED THREE-DIMENSIONAL POINT CLOUDS FROM NEAR-MONOSTATIC LASER SCANNERS USING COVARIANCE ANALYSIS
作者： Derek D. Lichti , Kwang-Ho Bae , David Belton
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摘要: Position uncertainty is one of the most important quantities an unorganised three-dimensional point clouds since it provides confidence level any parametric estimation such as surface normal vector and registration clouds. We present explicit form position based on covariance analysis a point. In addition, variance estimated algorithm to evaluate optimal size neighbourhood which minimises are presented.
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