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, 653–658, 2016
https://doi.org/10.5194/isprs-archives-XLI-B5-653-2016
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 653–658, 2016
https://doi.org/10.5194/isprs-archives-XLI-B5-653-2016

  16 Jun 2016

16 Jun 2016

INCORPORATION OF UNRELIABLE INFORMATION INTO PHOTOGRAMMETRIC RECONSTRUCTION FOR RECOVERY OF SCALE USING NON-PARAMETRIC BELIEF PROPAGATION

J. Hollick, P. Helmholz, and D. Belton J. Hollick et al.
  • Department of Spatial Sciences, Curtin University, Australia

Keywords: Sensor Fusion, Belief Propagation, Photogrammetry, Barometer, GNSS

Abstract. The creation of large photogrammetric models often encounter several difficulties in regards to geometric accuracy, scale and geolocation, especially when not using control points. Geometric accuracy can be a problem when encountering repetitive features, scale and geolocation can be challenging in GNSS denied or difficult to reach environments. Despite these challenges scale and location are often highly desirable even if only approximate, especially when the error bounds are known. Using non-parametric belief propagation we propose a method of fusing different sensor types to allow robust creation of scaled models without control points. Using this technique we scale models using only the sensor data sometimes to within 4% of their actual size even in the presence of poor GNSS coverage.