Fusion of laser scanning and Photogrammetric data for the documentation and VR visualization of an archaeological tomb complex

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Presented at the FIG Congress 2018, May 6-11, 2018 in Istanbul, Turkey Fusion of laser scanning and Photogrammetric data for the documentation and VR visualization of an archaeological tomb complex E. Friedli, J. Banz, Z. Gojcic and A. Wieser FIG Congress 2018 - Istanbul - Turkey 10.05.2018 1

Life Histories of Theban Tombs (LHTT) 1 Goal: 3D Digital Reality with large coverage and sub-mm resolution )1 Cooperation with Department of Ancient Civilizations, University of Basel, SNSF grant 162967, https://lhtt.philhist. unibas.ch/sheikh-abd-el-qurna FIG Congress 2018 - Istanbul - Turkey 10.05.2018 2

Approach Fusion of TLS, Photogrammetry and close-up scans Selective coverage with highest resolution Fotos: University of Basel, LHTT Photos: M. Kačičnik FIG Congress 2018 - Istanbul - Turkey 10.05.2018 3

Example: Narrow vertical shaft Challenge: Upper part not accessible with the scanner 10 m Solution: 8 scans of the shaft (ladder) 98 pictures with SLR camera mounted on a long pole for upper ¼ Feature-based registration of photogrammetric and TLS point clouds (overlap only 15%) University of Basel, LHTT Photo: K. Powroznik FIG Congress 2018 - Istanbul - Turkey 10.05.2018 4

Workflow TLS point cloud Photogrammetric point cloud Coarse scaling Coarse alignment Keypoint extraction (Harris3D) Fine alignment and scaling (ICP) Keypoint matching (K4-PCS) Registered point clouds FIG Congress 2018 - Istanbul - Turkey 10.05.2018 5

Results FIG Congress 2018 - Istanbul - Turkey 10.05.2018 6

Results 2 m 5 mm RMS horizontal cross section vertical cross section FIG Congress 2018 - Istanbul - Turkey 10.05.2018 7

Example: Funerary Chapel Challenge Fully textured 3D model despite poor illumination, surface roughness, and parts with little texture 9 m Solution TLS for geometry (80 scans) RGB pictures (7000) with SLR camera and flash for texture Fusion of TLS and photogrammetric point clouds after color adjustment and dense matching 18 m University of Basel, LHTT Map: G. Heindl, S. Stucky University of Basel, LHTT Photo: M. Kačičnik FIG Congress 2018 - Istanbul - Turkey 10.05.2018 8

Workflow 1 (Geometry) TLS point cloud Photogrammetric point cloud Coarse scaling Coarse alignment Keypoint extraction (Harris3D) Fine alignment and scaling (ICP) Keypoint matching (K4-PCS) Registered point clouds FIG Congress 2018 - Istanbul - Turkey 10.05.2018 9

Workflow 2 (Texture) TLS mesh Oriented and calibrated images Creation of texture atlas Textured TLS mesh FIG Congress 2018 - Istanbul - Turkey 10.05.2018 10

Texture Atlas Atlas FIG Congress 2018 - Istanbul - Turkey 10.05.2018 11

Workflow 3 (Reduction of resolution) Challenge: Resulting textured model too large for RT visualization (25M faces) Solution: Decimation of TLS mesh Calculation of bump maps New texture atlas: Shading from bump map plus original texture FIG Congress 2018 - Istanbul - Turkey 10.05.2018 12

Workflow 3 (Reduction of resolution) original resolution (25 Mio faces) decimated resolution (22k faces) decimated resolution (22k) with bump map from the original resolution FIG Congress 2018 - Istanbul - Turkey 10.05.2018 13

Conclusion Multi-modal data acquisition for generation of 3d models with appropriate properties Variety of sensors for obtaining point clouds and colors Key are coregistration and blending Presented herein purely data driven approach for scaling and registration RT visualization using techniques from gaming industry and CG FIG Congress 2018 - Istanbul - Turkey 10.05.2018 14