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Machine-learned Regularization and Polygonization of Building Segmentation Masks

Zorzi, Stefano and Bittner, Ksenia and Fraundorfer, Friedrich (2021) Machine-learned Regularization and Polygonization of Building Segmentation Masks. ICPR 2020, 10.- 15. Jan. 2021, Milano, Italien.

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We propose a machine learning based approach for automatic regularization and polygonization of building segmentation masks. Taking an image as input, we first predict building segmentation maps exploiting generic fully convolutional network (FCN). A generative adversarial network (GAN) is then involved to perform a regularization of building boundaries to make them more realistic, i.e., having more rectilinear outlines which construct right angles if required. This is achieved through the interplay between the discriminator which gives a probability of input image being true and generator that learns from discriminator's response to create more realistic images. Finally, we train the backbone convolutional neural network (CNN) which is adapted to predict sparse outcomes corresponding to building corners out of regularized building segmentation results. Experiments on three building segmentation datasets demonstrate that the proposed method is not only capable of obtaining accurate results, but also of producing visually pleasing building outlines parameterized as polygons.

Item URL in elib:https://elib.dlr.de/138210/
Document Type:Conference or Workshop Item (Speech)
Title:Machine-learned Regularization and Polygonization of Building Segmentation Masks
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Zorzi, Stefanozorzi (at) icg.tugraz.atUNSPECIFIED
Bittner, KseniaKsenia.Bittner (at) dlr.dehttps://orcid.org/0000-0002-4048-3583
Fraundorfer, Friedrichfraundorfer (at) icg.tugraz.athttps://orcid.org/0000-0002-5805-8892
Date:January 2021
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Series Name:International Conference on Pattern Recognition
Keywords:deep learning, building mask, polygonization, regularization
Event Title:ICPR 2020
Event Location:Milano, Italien
Event Type:international Conference
Event Dates:10.- 15. Jan. 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Bittner, Ksenia
Deposited On:27 Nov 2020 09:17
Last Modified:01 Mar 2021 03:00

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