Cumulative Assessment for Urban 3D Modeling

• URL: http://arxiv.org/abs/2107.04622v1
• Date: Fri, 9 Jul 2021 18:29:50 GMT
• Title: Cumulative Assessment for Urban 3D Modeling
• Authors: Shea Hagstrom, Hee Won Pak, Stephanie Ku, Sean Wang, Gregory Hager, Myron Brown
• Abstract summary: 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. We present a cumulative assessment metric that succinctly captures error contributions from each of these components.
• Score: 0.8155575318208631
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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