Radiometry propagation to large 3D point clouds from sparsely sampled ground truth

Thomas Höll

Research output: Contribution to conference(Old data) Lecture or PresentationResearchpeer-review

Abstract

Good radiometry of a 3D reconstruction is essential for digital conservation and versatile visualization of cultural heritage artifacts and sites. For large sites, "true" radiometry for the complete 3D point cloud is very expensive to obtain. We present a method that is capable to reconstruct the radiometric surface properties of an entire scene despite the fact that we only have access to the "true" radiometry of a small part of it. This is done in a two stage process: First, we transfer the radiometry to spatially corresponding parts of the scene, and second, we propagate these values to the entire scene using affinity information. We apply our method to 3D point clouds and 2D images, and show excellent quantitative and visually pleasing qualitative results. This approach can be of high value in many applications where users want to improve phototextured models towards high-quality yet affordable radiometry.
Original languageEnglish
Publication statusPublished - 20 Nov 2016

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Radiometry propagation to large 3D point clouds from sparsely sampled ground truth. / Höll, Thomas.

2016.

Research output: Contribution to conference(Old data) Lecture or PresentationResearchpeer-review

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AB - Good radiometry of a 3D reconstruction is essential for digital conservation and versatile visualization of cultural heritage artifacts and sites. For large sites, "true" radiometry for the complete 3D point cloud is very expensive to obtain. We present a method that is capable to reconstruct the radiometric surface properties of an entire scene despite the fact that we only have access to the "true" radiometry of a small part of it. This is done in a two stage process: First, we transfer the radiometry to spatially corresponding parts of the scene, and second, we propagate these values to the entire scene using affinity information. We apply our method to 3D point clouds and 2D images, and show excellent quantitative and visually pleasing qualitative results. This approach can be of high value in many applications where users want to improve phototextured models towards high-quality yet affordable radiometry.

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