Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks
Author:
Affiliation:
1. Technical University of Munich
2. Bruno Kessler Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10208270/10208119/10208594.pdf?arnumber=10208594
Reference57 articles.
1. AUTOMATIC EXTRACTION OF FACADES AND WINDOWS FROM MLS POINT CLOUDS USING VOXELSPACE AND VISIBILITY ANALYSIS
2. UNCERTAINTY REPRESENTATION AND QUANTIFICATION OF 3D BUILDING MODELS
3. FACADE RECONSTRUCTION FOR TEXTURED LOD2 CITYGML MODELS BASED ON DEEP LEARNING AND MIXED INTEGER LINEAR PROGRAMMING
4. TUM-MLS-2016: An Annotated Mobile LiDAR Dataset of the TUM City Campus for Semantic Point Cloud Interpretation in Urban Areas
5. A comprehensive framework for evaluating the quality of street view imagery
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1. From aerial LiDAR point clouds to multiscale urban representation levels by a parametric resampling;Computers & Graphics;2024-10
2. A framework for fully automated reconstruction of semantic building model at urban-scale using textured LoD2 data;ISPRS Journal of Photogrammetry and Remote Sensing;2024-10
3. Low-Cost Data, High-Quality Models: A Semi-Automated Approach to LOD3 Creation;ISPRS International Journal of Geo-Information;2024-04-03
4. Modeling the Geometry of Tree Trunks Using LiDAR Data;Forests;2024-02-16
5. MLS2LoD3: Refining Low LoDs Building Models with MLS Point Clouds to Reconstruct Semantic LoD3 Building Models;Lecture Notes in Geoinformation and Cartography;2024
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