Data for LookUp3D: Data-Driven 3D Scanning
Creators
Description
This deposit contains captured and processed data for LookUp3D, a novel calibration and reconstruction procedure for structured light scanning that foregoes explicit point triangulation in favor of a data-driven lookup procedure. The key idea is to sweep a calibration checkerboard over the entire scanning volume with a linear stage and acquire a dense stack of images to build a per-pixel lookup table from colors to depths. Imperfections in the setup, lens distortion, and sensor defects are baked into the calibration data, leading to a more reliable and accurate reconstruction.
Captured data is provided in TIFF or JPEG file formats, along with the calibrated lookup table files in numpy-specific file formats and a JSON configuration file. Processed data is provided as point clouds (ASCII .ply files) corresponding to figures presented in the paper (plus additional examples) and OBJ (.obj) files used to measure error.
Files
README.md
Files
(41.1 GB)
| Name | Size | Download all |
|---|---|---|
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data.zip
md5:a5a6f023d080be1ff0858e969ea56b72
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39.3 GB | Preview Download |
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point_clouds.zip
md5:833a735d209fc2f691cf999b0f0bc565
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1.7 GB | Preview Download |
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README.md
md5:2b10832e77bbe6c6d0f775a6435a0866
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4.1 kB | Preview Download |
Additional details
Related works
- Is supplement to
- Preprint: arXiv:2405.14882 (arXiv)
- Requires
- Software: https://www.github.com/geometryprocessing/scanner (URL)
Funding
- Collaborative Research: Differentiable Dynamic Simulation on Complex Geometries for Parameter Inference, Design Optimization and Control OAC-2411349
- National Science Foundation
- Collaborative Research: Frameworks: Cyberinfrastructure to Catalyze and Sustain the Urban Computing Community OAC-2411221
- National Science Foundation
Dates
- Created
-
2025