Volume XLII-2/W15
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W15, 1195–1201, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W15-1195-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W15, 1195–1201, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W15-1195-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  26 Aug 2019

26 Aug 2019

SOFTWARE COMPARISON FOR UNDERWATER ARCHAEOLOGICAL PHOTOGRAMMETRIC APPLICATIONS

M. Vlachos1, L. Berger2, R. Mathelier2, P. Agrafiotis1, and D. Skarlatos1 M. Vlachos et al.
  • 1Cyprus University of Technology, Dep. Of Civil Engineering and Geomatics, P.O. Box 50329, Limassol 3603, Cyprus
  • 2National School of Geographic Sciences (ENSG), France

Abstract. This paper presents an investigation as to whether and how the selection of the SfM-MVS software affects the 3D reconstruction of submerged archaeological sites. Specifically, Agisoft Photoscan, VisualSFM, SURE, 3D Zephyr and Reality Capture software were used and evaluated according to their performance in 3D reconstruction using specific metrics over the reconstructed underwater scenes. It must be clarified that the scope of this study is not to evaluate specific algorithms or steps that the various software use, but to evaluate the final results and specifically the generated 3D point clouds. To address the above research issues, a dataset from the ancient shipwreck, laying at 45 meters below sea level, is used. The dataset is composed of 19 images having very small camera to object distance (1 meter), and 42 images with higher camera to object distance (3 meters) images. Using a common bundle adjustment for all 61 images, a reference point cloud resulted from the lower dataset is used to compare it with the point clouds of the higher dataset generated using the different photogrammetric packages. Following that, a comparison regarding the number of total points, cloud to cloud distances, surface roughness, surface density and a combined 3D metric was done to evaluate and see which one performed the best.