Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 851-859, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-851-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
06 Jun 2016
EVALUATION OF THE QUALITY OF ACTION CAMERAS WITH WIDE-ANGLE LENSES IN UAV PHOTOGRAMMETRY
H. Hastedt, T. Ekkel, and T. Luhmann IAPG, Jade University of Applied Sciences, Ofener Str. 16/19, 26121 Oldenburg, Germany
Keywords: camera calibration, Computer Vision, GoPro, accuracy, interior orientation, fish-eye, UAV Abstract. The application of light-weight cameras in UAV photogrammetry is required due to restrictions in payload. In general, consumer cameras with normal lens type are applied to a UAV system. The availability of action cameras, like the GoPro Hero4 Black, including a wide-angle lens (fish-eye lens) offers new perspectives in UAV projects. With these investigations, different calibration procedures for fish-eye lenses are evaluated in order to quantify their accuracy potential in UAV photogrammetry. Herewith the GoPro Hero4 is evaluated using different acquisition modes. It is investigated to which extent the standard calibration approaches in OpenCV or Agisoft PhotoScan/Lens can be applied to the evaluation processes in UAV photogrammetry. Therefore different calibration setups and processing procedures are assessed and discussed. Additionally a pre-correction of the initial distortion by GoPro Studio and its application to the photogrammetric purposes will be evaluated. An experimental setup with a set of control points and a prospective flight scenario is chosen to evaluate the processing results using Agisoft PhotoScan. Herewith it is analysed to which extent a pre-calibration and pre-correction of a GoPro Hero4 will reinforce the reliability and accuracy of a flight scenario.
Conference paper (PDF, 981 KB)


Citation: Hastedt, H., Ekkel, T., and Luhmann, T.: EVALUATION OF THE QUALITY OF ACTION CAMERAS WITH WIDE-ANGLE LENSES IN UAV PHOTOGRAMMETRY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 851-859, https://doi.org/10.5194/isprs-archives-XLI-B1-851-2016, 2016.

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