Robust resection model for aligning the mobile mapping systems trajectories at degraded and denied urban environments

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Abstract

Mobile mapping systems MMS equipped with cameras and laser scanners are widely used nowadays for different geospatial applications with centimetric accuracy either in project wise or national wise scales. The achieved positioning accuracy is very much related to the navigation unit, namely the GNSS and IMU onboard. Accordingly, in GNSS denied and degraded environments, the absolute positioning accuracy is worsened to few meters in some cases. Frequently, ground control points GCPs of a high positioning accuracy are used to align the MMS trajectories and to improve the accuracy when needed.

The best way to integrate the MMS trajectories to the GCPs is by measuring them on the MMS images where the positioning accuracy is dropped. MMS images are mostly spherical panoramic (equirectangular) images and sometimes perspective and, in both types, it is required to precisely determine the images orientation in what is called as space resection or camera pose determination. For perspective images, the pose is conventionally determined by collinearity equations or by using projection and fundamental matrices. Whereas for equirectangular panoramic images it is based on resecting vertical and horizontal angles. However, there is still a challenge in the state–of–the–art of image pose determination because of the model nonlinearity and the sensitivity to proper initialization and spatial distribution of the points.

In this research, a generic method is presented to solve the pose resection problem for the perspective and equirectangular images using oblique angles. The oblique angles are derived from the measured image coordinates and based on spherical trigonometry rules and vector geometry. The developed algorithm has proven to be highly stable and steadily converge to the global minimum. This is related to the robust geometric constraint offered by the oblique angles that are enclosed between the object points and the camera. As a result, the MMS trajectories are realigned accurately to the GCPs and the absolute accuracy is highly refined. Four experimental tests are presented where the results show the efficiency of the proposed angular based model in different cases of simulated and real data with different image types
Original languageEnglish
Title of host publicationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Subtitle of host publicationXXIV ISPRS Congress
EditorsN. Paparoditis, C. Mallet, F. Lafarge, S. Hinz, R. Feitosa, M. Weinmann, B. Jutzi
PublisherInternational Society for Photogrammetry and Remote Sensing (ISPRS)
Pages215–222
Number of pages8
VolumeV-1-2020
DOIs
Publication statusPublished - 3 Aug 2020
EventXXIVth ISPRS Congress 2020 - Nice-Acropolis Congress and Exhibition Centre, Nice, France
Duration: 4 Jul 202010 Jul 2020
Conference number: 24
http://www.isprs2020-nice.com

Publication series

NameISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
PublisherCopernicus
ISSN (Print)2194-9042

Conference

ConferenceXXIVth ISPRS Congress 2020
Abbreviated titleISPRS 2020
CountryFrance
CityNice
Period4/07/2010/07/20
Internet address

Keywords

  • mobile mapping systems
  • equirectangular image
  • exterior orientation
  • camera pose
  • oblique angle
  • image resection

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    Alsadik, B. (2020). Robust resection model for aligning the mobile mapping systems trajectories at degraded and denied urban environments. In N. Paparoditis, C. Mallet, F. Lafarge, S. Hinz, R. Feitosa, M. Weinmann, & B. Jutzi (Eds.), ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences: XXIV ISPRS Congress (Vol. V-1-2020, pp. 215–222). (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences). International Society for Photogrammetry and Remote Sensing (ISPRS). https://doi.org/10.5194/isprs-annals-V-1-2020-215-2020