The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XXXIX-B5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B5, 453–458, 2012
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B5, 453–458, 2012

  30 Jul 2012

30 Jul 2012


J. Burkhard, S. Cavegn, A. Barmettler, and S. Nebiker J. Burkhard et al.
  • Institute of Geomatics Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland

Keywords: Mobile, Mapping, Stereoscopic, Multisensor, Georeferencing, Radiometric, Calibration, Matching

Abstract. In this paper we introduce a state-of-the-art stereovision mobile mapping system with different stereo imaging sensors and present a series of performance tests carried out with this system. The aim of these empirical tests was to investigate different performance aspects under real-world conditions. The investigations were carried out with different cameras and camera configurations in order to determine their potential and limitations for selected application scenarios. In brief the test set consists of investigations in geometric accuracy, in radiometric image quality and in the extraction of 3d point clouds using dense matching algorithms. The first tests resulted in an absolute overall 3d accuracy of 4-5 cm depending mainly on the quality of the navigation system used for direct georeferencing. The relative point measurement accuracy was approx. 2 cm and 1 cm for the 2 megapixel and the 11 megapixel sensors respectively. In the second series of investigations we present results obtained by applying tone mapping algorithms often used for high dynamic range images (HDR). In our third series of tests refinements of the radiometric calibration of the stereo system and corrections of the vignetting resulted in an improved completeness of the depth map on the roadside environment. We conclude the paper with investigations in obtaining complete and accurate depth maps for a robust and accurate 3d monoplotting support in vision-based mobile mapping web services. For this we present first results obtained by interpolating incomplete areas in the disparity maps and by fusing the disparity maps with additional LiDAR data.