BIP! Finder - Detection Of Collapsed Buildings By Classifying Segmented Airborne Laser Scanner Data

2012 • Detection Of Collapsed Buildings By Classifying Segmented Airborne Laser Scanner Data

Authors: S. A. Fathi; Sander Oude Elberink; Moreblessings Shoko; Martin Rutzinger

Venue: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Type: Publication

Abstract: Abstract. Rapid mapping of damaged regions and individual buildings is essential for efficient crisis management. Airborne laser scanner (ALS) data is potentially able to deliver accurate information on the 3D structures in a damaged region. In this paper we describe two different strategies how to process ALS point clouds in order to detect collapsed buildings automatically. Our aim is to detect collapsed buildings using post event data only. The first step in the workflow is the segmentation of the point cloud detecting planar regions. Next, ... (read more)

Impact:

6.3554766E-9 5.2784075E-9 17 7

/ Attention: 0 12

Topics: Artificial intelligence Data mining Computer vision

DOI: 10.5194/isprsarchives-xxxviii-5-w12-307-2011

External links: Crossref OpenAIRE

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