Change detection in cadastral 3D models and point clouds and its use for improved texturing

Sander Klomp, Bas Boom, Thijs M.B. van Lankveld, Peter de With

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Abstract

By combining terrestrial panorama images and aerial imagery, or using LiDAR, large 3D point clouds can be generated for 3D city modeling. We describe an algorithm for change detection in point clouds, including three new contributions: change detection for LOD2 models compared to 3D point clouds, the application of detected changes for creating extended and textured LOD2 models, and change detection between point clouds of different years. Overall, LOD2 model-to-point-cloud changes are reliably found in practice, and the algorithm achieves a precision of 0.955 and recall of 0.983 on a synthetic dataset. Despite not having a watertight model, texturing results are visually promising, improving over directly textured LOD2 models.
Original languageEnglish
Title of host publicationElectronic Imaging
Subtitle of host publicationIntelligent Robotics and Industrial Applications using Computer Vision 2019
PublisherIS&T
Number of pages7
DOIs
Publication statusPublished - 13 Jan 2019
EventElectronic Imaging: Intelligent Robotics and Industrial Applications using Computer Vision 2019 - Hyatt Regency San Francisco Airport, Burlingame, United States
Duration: 13 Jan 201917 Jan 2019

Conference

ConferenceElectronic Imaging
CountryUnited States
CityBurlingame
Period13/01/1917/01/19

Keywords

  • 3D model
  • Cadaster
  • Change detection
  • City modeling
  • Point cloud

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    Klomp, S., Boom, B., van Lankveld, T. M. B., & de With, P. (2019). Change detection in cadastral 3D models and point clouds and its use for improved texturing. In Electronic Imaging: Intelligent Robotics and Industrial Applications using Computer Vision 2019 [455] IS&T. https://doi.org/10.2352/ISSN.2470-1173.2019.7.IRIACV-455