Cumulative Assessment for Urban 3D Modeling

Cumulative Assessment for Urban 3D Modeling

Urban 3D modeling from satellite images requires accurate semantic segmentation to delineate urban features, multiple view stereo for 3D reconstruction of surface heights, and 3D model fitting to produce compact models with accurate surface slopes. In this work, we present a cumulative assessment me...

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Veröffentlicht in:arXiv.org 2021-07
Hauptverfasser: Hagstrom, Shea, Pak, Hee Won, Ku, Stephanie, Wang, Sean, Hager, Gregory, Brown, Myron
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Image reconstruction
Image segmentation
Modelling
Satellite imagery
Three dimensional models
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Pak, Hee Won
Ku, Stephanie
Wang, Sean
Hager, Gregory
Brown, Myron
description Urban 3D modeling from satellite images requires accurate semantic segmentation to delineate urban features, multiple view stereo for 3D reconstruction of surface heights, and 3D model fitting to produce compact models with accurate surface slopes. In this work, we present a cumulative assessment metric that succinctly captures error contributions from each of these components. We demonstrate our approach by providing challenging public datasets and extending two open source projects to provide an end-to-end 3D modeling baseline solution to stimulate further research and evaluation with a public leaderboard.
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subjects Image reconstruction
Image segmentation
Modelling
Satellite imagery
Three dimensional models
title Cumulative Assessment for Urban 3D Modeling
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