This paper, by an international group of researchers proposes a robust and efficient segmentation methodology for abstraction of an enormous number of laser points into plane information.
They are claiming very impressive results, “The experimental results demonstrate, through both qualitative and quantitative evaluations, the outcomes’ high level of reliability. The proposed segmentation algorithm provided 96.89% overall correctness, 95.84% completeness, a 0.25 m overall mean value of centroid difference, and less than 1° of angle difference. ”
A neighborhood definition based on the shape of the surface increases the homogeneity of the laser point attributes. The magnitude of the normal position vector is used as an attribute for reducing the dimension of the accumulator array.
This kind of research can lead to improvements in automated feature extraction.