The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLI-B5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 741–747, 2016
https://doi.org/10.5194/isprs-archives-XLI-B5-741-2016
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 741–747, 2016
https://doi.org/10.5194/isprs-archives-XLI-B5-741-2016

  16 Jun 2016

16 Jun 2016

INTEGRATING SMARTPHONE IMAGES AND AIRBORNE LIDAR DATA FOR COMPLETE URBAN BUILDING MODELLING

Shenman Zhang1, Jie Shan2, Zhichao Zhang1, Jixing Yan1, and Yaolin Hou1 Shenman Zhang et al.
  • 1School of Remote Sensing and Information Engineering, Wuhan University, 430079, Wuhan, China
  • 2Lyles School of Civil Engineering, Purdue University, 47907, West Lafayette, IN, USA

Keywords: Smartphone Images, Airborne LiDAR, Building Reconstruction, Registration

Abstract. A complete building model reconstruction needs data collected from both air and ground. The former often has sparse coverage on building façades, while the latter usually is unable to observe the building rooftops. Attempting to solve the missing data issues in building reconstruction from single data source, we describe an approach for complete building reconstruction that integrates airborne LiDAR data and ground smartphone imagery. First, by taking advantages of GPS and digital compass information embedded in the image metadata of smartphones, we are able to find airborne LiDAR point clouds for the corresponding buildings in the images. In the next step, Structure-from-Motion and dense multi-view stereo algorithms are applied to generate building point cloud from multiple ground images. The third step extracts building outlines respectively from the LiDAR point cloud and the ground image point cloud. An automated correspondence between these two sets of building outlines allows us to achieve a precise registration and combination of the two point clouds, which ultimately results in a complete and full resolution building model. The developed approach overcomes the problem of sparse points on building façades in airborne LiDAR and the deficiency of rooftops in ground images such that the merits of both datasets are utilized.