Least-squares building model fitting using aerial photos and LiDAR data

Sendo Wang*, Yi Hsing Tseng, Ayman F. Habib

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Building models are conventionally reconstructed by measuring their vertices point-by-point in a digital photogrammetric workstation (DPW), which is time and labor consuming process. Although aerial photos implicitly provide 3D information of buildings, LiDAR systems directly provide high density and accurate point cloud coordinates. However, LiDAR data cannot accurately represent the building boundaries. To take advantage of both systems, we propose Floating Model and a tailored least-squares model-data fitting (LSMDF) algorithm in this paper. The floating model is a pre-defined primitive model, which is described by a set of parameters, floating in the space. A building is reconstructed by adjusting these model parameters so the wire-frame model adequately fits the building's boundary in all overlapping photos and LiDAR data. The semi-automated modeling procedure consists of 3 steps. First, the operator chooses an appropriate model and approximately fit it to the building's outlines on the aerial photos. Then, an automated procedure computes the optimal fit between the models and both of aerial photos and LiDAR data using an iterative LSMDF algorithm. Finally, the model parameters and standard deviations are provided, and the wire-frame model is superimposed on all overlapping aerial photos for the operator to check or modify the results. To test the proposed algorithm and approach, an image block of 4 panchromatic aerial photos and corresponding LiDAR data are selected for the experiments. The ground resolution of the image is approximately 5cm. The point density of LiDAR point cloud is about 4-5point/m 2. The reconstructed models are manually evaluated and compared. Most of the buildings are accurately modeled, and the fitting result achieves the photogrammetric accuracy. In addition, the implicit constraints within the model, such as the parallel edges or rectangle corners, will keep the building shape without distortion.

Original languageEnglish
Title of host publicationAmerican Society for Photogrammetry and Remote Sensing Annual Conference 2010
Subtitle of host publicationOpportunities for Emerging Geospatial Technologies
Pages956-969
Number of pages14
Publication statusPublished - 2010
Externally publishedYes
EventAmerican Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies - San Diego, CA, United States
Duration: 2010 Apr 262010 Apr 30

Publication series

NameAmerican Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies
Volume2

Conference

ConferenceAmerican Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies
Country/TerritoryUnited States
CitySan Diego, CA
Period2010/04/262010/04/30

ASJC Scopus subject areas

  • Information Systems
  • Computers in Earth Sciences

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