loading
Documents

Research.Publish.Connect.

Paper

Authors: Lukas Lucks ; Dimitri Bulatov ; Ulrich Thönnessen and Melanie Böge

Affiliation: Fraunhofer Institute of Optronics, System Technologies and Image Exploitation Gutleuthausstr. 1, 76275 Ettlingen and Germany

ISBN: 978-989-758-354-4

ISSN: 2184-4321

Keyword(s): Damage Detection, Superpixels, Feature Extraction, Random Forest, Classification.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Segmentation and Grouping

Abstract: Surveying buildings that are damaged by natural disasters, in particular, assessment of roof damage, is challenging, and it is costly to hire loss adjusters to complete the task. Thus, to make this process more feasible, we developed an automated approach for assessing roof damage from post-loss close-range aerial images and roof outlines. The original roof area is first delineated by aligning freely available building outlines. In the next step, each roof area is decomposed into superpixels that meet conditional segmentation criteria. Then, 52 spectral and textural features are extracted to classify each superpixel as damaged or undamaged using a Random Forest algorithm. In this way, the degree of roof damage can be evaluated and the damage grade can be computed automatically. The proposed approach was evaluated in trials with two datasets that differed significantly in terms of the architecture and degree of damage. With both datasets, an assessment accuracy of about 90% was attaine d on the superpixel level for roughly 800 buildings. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.237.138.69

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Lucks, L.; Bulatov, D.; Thönnessen, U. and Böge, M. (2019). Superpixel-wise Assessment of Building Damage from Aerial Images.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, ISBN 978-989-758-354-4, ISSN 2184-4321, pages 211-220. DOI: 10.5220/0007253802110220

@conference{visapp19,
author={Lukas Lucks. and Dimitri Bulatov. and Ulrich Thönnessen. and Melanie Böge.},
title={Superpixel-wise Assessment of Building Damage from Aerial Images},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,},
year={2019},
pages={211-220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007253802110220},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,
TI - Superpixel-wise Assessment of Building Damage from Aerial Images
SN - 978-989-758-354-4
AU - Lucks, L.
AU - Bulatov, D.
AU - Thönnessen, U.
AU - Böge, M.
PY - 2019
SP - 211
EP - 220
DO - 10.5220/0007253802110220

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.