Volume XLII-1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 167-171, 2018
https://doi.org/10.5194/isprs-archives-XLII-1-167-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 167-171, 2018
https://doi.org/10.5194/isprs-archives-XLII-1-167-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  26 Sep 2018

26 Sep 2018

MOBILE MAPPING SYSTEM BASED ON ACTION CAMERAS

J. A. Gonçalves and A. Pinhal J. A. Gonçalves and A. Pinhal
  • Science Faculty, University of Porto, Rua Campo Alegre, 4169-004 Porto, Portugal

Keywords: mobile mapping, action camera, GNSS, camera calibration, direct georeferencing

Abstract. Action cameras can operate in outdoor conditions, such as outside a car, and provide good quality imagery that can be exploited to collect geospatial data by photogrammetric means. Recent models include GPS, which can deliver position and time of individual images and video frames. That is the case of the very popular camera, Gopro Hero 5. This paper describes the implementation of a mobile mapping system, based on a GoPro Hero 5 camera mounted on the side rearview mirror of a car. Although the system can be dependent on the camera GPS positions only, it was developed to include a GNSS dual frequency receiver, carried inside the car, on the dashboard. Within good observation conditions, without tall buildings, differential positioning (either RTK or PPK) provides the trajectory with accuracy of a few centimetres. The precise time of individual frames is obtained from the camera GPS and positions are interpolated from the GNSS receiver. Assuming the car moves in a horizontal plane and the camera has no significant tilts, the system is treated in planimetric terms, with camera axis azimuth derived from the vehicle trajectory. Positions of observed objects, such as traffic signs, are derived from consecutive frames. Tests carried out in a sparse urban environment have shown planimetric accuracy better than 40 cm, appropriate for large scale mapping, such as 1 : 2000. The system can be improved in several forms, through processing techniques, such as structure from motion, but without the incorporation of additional hardware.