Abstract
This paper presents a method of segmentation of a point cloud into individual objects. The described method is based on using the data on the intensities of the reflected signals obtained by laser scanning. To accelerate the calculations, the point cloud is preliminarily partitioned into non-overlapping sets, superpixels. The objects are segmented by merging the superpixels and taking account of two features: the distance between the histograms of the intensity distribution and the coordinates of the points. To improve the quality of segmentation, three-dimensional filtering using a low-frequency Gabor filter is suggested. The calculation results and an analysis of the effectiveness of the proposed method are given.
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