한국측량학회지 (Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)

  • 제37권5호
  • /
  • Pages.331-341
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  • 2019
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  • 1598-4850(pISSN)
  • /
  • 2288-260X(eISSN)
한국측량학회 (Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)
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Updating Smartphone's Exterior Orientation Parameters by Image-based Localization Method Using Geo-tagged Image Datasets and 3D Point Cloud as References

  • Wang, Ying Hsuan (Dept. of Civil and Environmental Engineering, Yonsei University) ;
  • Hong, Seunghwan (Stryx Inc.) ;
  • Bae, Junsu (Dept. of Civil and Environmental Engineering, Yonsei University) ;
  • Choi, Yoonjo (Dept. of Civil and Environmental Engineering, Yonsei University) ;
  • Sohn, Hong-Gyoo (Dept. of Civil and Environmental Engineering, Yonsei University)
  • 투고 : 2019.09.24
  • 심사 : 2019.10.11
  • 발행 : 2019.10.31
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초록

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.

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참고문헌

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