Comprehensive comparison of two image-based point clouds from aerial photos with airborne lidar for large-scale mapping: Door detection to envelope reconstruction

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9 Citations (Scopus)
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Abstract

The integration of computer vision and photogrammetry to generate three-dimensional (3D) information from images has contributed to a wider use of point clouds, for mapping purposes. Large-scale topographic map production requires 3D data with high precision and accuracy to represent the real conditions of the earth surface. Apart from LiDAR point clouds, the image-based matching is also believed to have the ability to generate reliable and detailed point clouds from multiple-view images. In order to examine and analyze possible fusion of LiDAR and image-based matching for large-scale detailed mapping purposes, point clouds are generated by Semi Global Matching (SGM) and by Structure from Motion (SfM). In order to conduct comprehensive and fair comparison, this study uses aerial photos and LiDAR data that were acquired at the same time. Qualitative and quantitative assessments have been applied to evaluate LiDAR and image-matching point clouds data in terms of visualization, geometric accuracy, and classification result. The comparison results conclude that LiDAR is the best data for large-scale mapping.

Original languageEnglish
Title of host publicationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
PublisherISPRS
Pages557-565
VolumeXLII-2/W7
DOIs
Publication statusPublished - 2017
EventISPRS Geospatial Week 2017 - Wuhan, China
Duration: 18 Sep 201722 Sep 2017
http://www.isprs.org/documents/geoweek.aspx

Conference

ConferenceISPRS Geospatial Week 2017
CountryChina
CityWuhan
Period18/09/1722/09/17
Internet address

Keywords

  • Combinatorial geometry
  • Completeness
  • Connectivity
  • Energy minimization
  • Trajectory

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