Abstract: Abstract Point clouds generated from airborne oblique images have become a suitable source for detailed building damage assessment after a disaster event, since they provide the essential geometric and radiometric features of both roof and facades of the building. However, they often contain gaps that result either from physical damage or from a range of image artefacts or data acquisition conditions. A clear understanding of those reasons, and accurate classification of gap-type, are critical for 3D geometry-based damage assessment. In this st...
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Topics: 
Artificial intelligence
Remote sensing
Computer vision