Published September 25, 2026 | Version 1.1.0

ODD INN multistate photogrammetry and Unreal Engine evidence and retrospective analyses

Authors/Creators

Contributors

Data curator:

  • 1. ODD INN Sp. z o.o.

Description

ODD INN developed a workflow for acquiring the same physical objects in different states, establishing geometric correspondence between independently reconstructed meshes in Blender, and controlling geometry and material transitions in Unreal Engine 5. The project included seasonal digitisation of an open-air museum and interactive demonstrations.

Version 1.1.0 expands the documentary and retrospective evidence retained from version 1.0.1 with recovered historical source code and research data: OddInn Tools Blender addon versions 0.4.1, 0.5.0 and 1.0.0; validation notebooks and explicitly separated portability adaptations; geometry and saved validation results for three KM3 cases; the MS05 CSV collection; native Blender scenes; archived MS07 image pairs; a pair of seasonal cottage mesh exports with textures and reconstruction metadata; and selected editable Unreal Engine morph, snow-control and state-saving components with project source. The release documentation specifies the contents, dependencies, source versions, transformations and checksums of each package.

Recovered files are historical project outputs. Archive recovery and static integrity checks are not new experimental measurements or a verified end-to-end rerun. Full photographic reconstruction inputs, the complete demonstration game and original frame-time traces are not included in this version. The archived MS07 views have not been established as the complete input set for the final image-validation reports.

Use the version 1.1.0 README and file-scoped licence schedule for the new packages. The retained version 1.0.1 archive and its licence schedule describe that earlier evidence package only. Third-party software dependencies retain their own terms.

Files

README_v1.1.0.md

Files (1.1 GB)

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Additional details

Related works

Is supplemented by
Dataset: 10.5281/zenodo.22961577 (DOI)

Funding

Narodowe Centrum Badań i Rozwoju
POIR.01.01.01-00-0280/22-00