Abstract: This paper presents an algorithm for the segmentation of airborne laser scanning data. The segmentation is based on cluster analysis in a feature space. To improve the quality of the computed attributes, a recently proposed neighborhood system, called slope adaptive, is utilized. Key parameters of the laser data, e.g., point density, measurement accuracy, and horizontal and vertical point distribution, are used for defining the neighborhood among the measured points. Accounting for these parameters facilitates the computation of accurate and re...
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Topics: 
Artificial intelligence
Computer vision
Remote sensing