Structural Approach for Building Reconstruction from a Single DSM

Authors:
Florent Lafarge;Xavier Descombes;Josiane Zerubia;Marc Pierrot-Deseilligny
Affiliations:
Ariana Research Group, INRIA and Matis Laboratory, French Mapping Agency, Sophia Antipolis;Ariana Research Group, INRIA, Sophia Antipolis;Ariana Research Group, INRIA, Sophia Antipolis;French Mapping Agency (IGN), Saint-Mandé
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2010

Citing 0
Cited 5

A marked point process for modeling lidar waveforms

IEEE Transactions on Image Processing
Hierarchical multispectral galaxy decomposition using a MCMC algorithm with multiple temperature simulated annealing

Pattern Recognition
3D building roof reconstruction from point clouds via generative models

Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation

International Journal of Computer Vision
Semantic decomposition and reconstruction of residential scenes from LiDAR data

ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings

Quantified Score

Hi-index	0.14

Visualization

Abstract

We present a new approach for building reconstruction from a single Digital Surface Model (DSM). It treats buildings as an assemblage of simple urban structures extracted from a library of 3D parametric blocks (like a LEGO set). First, the 2D-supports of the urban structures are extracted either interactively or automatically. Then, 3D-blocks are placed on the 2D-supports using a Gibbs model which controls both the block assemblage and the fitting to data. A Bayesian decision finds the optimal configuration of 3D--blocks using a Markov Chain Monte Carlo sampler associated with original proposition kernels. This method has been validated on multiple data set in a wide-resolution interval such as 0.7 m satellite and 0.1 m aerial DSMs, and provides 3D representations on complex buildings and dense urban areas with various levels of detail.