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LOD Generation for Urban Scenes

Published: 08 May 2015 Publication History
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  • Abstract

    We introduce a novel approach that reconstructs 3D urban scenes in the form of levels of detail (LODs). Starting from raw datasets such as surface meshes generated by multiview stereo systems, our algorithm proceeds in three main steps: classification, abstraction, and reconstruction. From geometric attributes and a set of semantic rules combined with a Markov random field, we classify the scene into four meaningful classes. The abstraction step detects and regularizes planar structures on buildings, fits icons on trees, roofs, and facades, and performs filtering and simplification for LOD generation. The abstracted data are then provided as input to the reconstruction step which generates watertight buildings through a min-cut formulation on a set of 3D arrangements. Our experiments on complex buildings and large-scale urban scenes show that our approach generates meaningful LODs while being robust and scalable. By combining semantic segmentation and abstraction, it also outperforms general mesh approximation approaches at preserving urban structures.

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    Published In

    cover image ACM Transactions on Graphics
    ACM Transactions on Graphics  Volume 34, Issue 3
    April 2015
    152 pages
    ISSN:0730-0301
    EISSN:1557-7368
    DOI:10.1145/2774971
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

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    Publication History

    Published: 08 May 2015
    Accepted: 01 February 2015
    Revised: 01 December 2014
    Received: 01 April 2014
    Published in TOG Volume 34, Issue 3

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    Author Tags

    1. Markov random field
    2. Urban reconstruction
    3. abstraction
    4. arrangement of planes
    5. iconization
    6. levels of detail
    7. min-cut formulation

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    • Research-article
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    Funding Sources

    • ERC Starting Grant "Robust Geometry Processing" (257474)

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    • (2024)StructuredMesh: 3-D Structured Optimization of Façade Components on Photogrammetric Mesh Models Using Binary Integer ProgrammingIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2023.334849262(1-12)Online publication date: 2024
    • (2024) UMeshSegNet: Semantic Segmentation of 3D Mesh Generated from UAV Photogrammetry * 2024 IEEE 18th International Conference on Control & Automation (ICCA)10.1109/ICCA62789.2024.10591843(388-393)Online publication date: 18-Jun-2024
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