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GEOMETRIC FEATURES AND THEIR RELEVANCE FOR 3D POINT CLOUD CLASSIFICATION
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
In this paper, we focus on the automatic interpretation of 3D point cloud data in terms of associating a class label to each 3D point. While much effort has recently been spent on this research topic, little attention has been paid to the influencing factors that affect the quality of the derived classification results. For this reason, we investigate fundamental influencing factors making geometric features more or less relevant with respect to the classification task. We present a frameworkdoi:10.5194/isprs-annals-iv-1-w1-157-2017 fatcat:d6xit77zgbh7xezizuskdnlb4y