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RAPter: Rebuilding Man-made Scenes with Regular Arrangements of Planes

Abstract : With the proliferation of acquisition devices, gathering massive volumes of 3D data is now easy. Processing such large masses of pointclouds, however, remains a challenge. This is particularly a problem for raw scans with missing data, noise, and varying sampling density. In this work, we present a simple, scalable, yet powerful data reconstruction algorithm. We focus on reconstructing man-made scenes as regular arrangements of planes (RAP), thereby selecting both local plane-based approximations along with their global inter-plane relations. We propose a novel selection formulation to directly balance between data fitting and the simplicity of the resulting arrangement of extracted planes. The main technical contribution is a formulation that allows less-dominant orientations to still retain their internal regularity, and not being overwhelmed and regularized by the dominant scene orientations. We evaluate our approach on a variety of complex 2D and 3D pointclouds, and demonstrate the advantages over existing alternative methods.
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https://hal.inria.fr/hal-01498225
Contributor : Nicolas Mellado <>
Submitted on : Wednesday, March 29, 2017 - 5:15:38 PM
Last modification on : Saturday, June 20, 2020 - 3:37:51 AM
Document(s) archivé(s) le : Friday, June 30, 2017 - 4:54:21 PM

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Aron Monszpart, Nicolas Mellado, Gabriel Brostow, Niloy Mitra. RAPter: Rebuilding Man-made Scenes with Regular Arrangements of Planes. ACM Transactions on Graphics, Association for Computing Machinery, 2015, 34, pp.12. ⟨10.1145/2766995⟩. ⟨hal-01498225⟩

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