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Representing living architecture through skeleton reconstruction from point clouds

Middleton W, Shu Q, Ludwig F.

Scientific reports · 28 Jan 2022 · 10.1038/s41598-022-05194-y

Abstract

Living architecture, changing in structure with annual growth, requires precise, regular characterisation. However, its geometric irregularity and topological complexity make documentation using traditional methods difficult and presents challenges in creating useful models for mechanical and physiological analyses. Two kinds of living architecture are examined: historic living root bridges grown in Meghalaya, India, and contemporary 'Baubotanik' structures designed and grown in Germany. These structures exhibit common features, in particular network-like structures of varying complexity that result from inosculations between shoots or roots. As an answer to this modelling challenge, we present the first extensive documentation of living architecture using photogrammetry and a subsequent skeleton extraction workflow that solves two problems related to the anastomoses and varying nearby elements specific to living architecture. Photogrammetry was used as a low cost method, supplying detailed point clouds of the structures' visible surfaces. A workflow based on voxel-thinning (using deletion templates and adjusted p-simplicity criteria) provides efficient, accurate skeletons. A volume reconstruction method is derived from the thinning process. The workflow is assessed on seven characteristics beneficial in representing living architecture in comparison with alternative skeleton extraction methods. The resulting models are ready for use in analytical tools, necessary for functional, responsible design.

Code and data availability

The paper's Data availability statement explicitly provides public access to the authors' skeletonisation source code on GitHub and the photogrammetric point clouds (Freiburg pavilion, Ficus joint, Baubotanik joint) on the TUM media repository. Both are paper-specific, public, and actionable.

Codepublic

The source code is available at: https://github.com/QiguanShu/skeleton-abstraction-of-point-cloud-by-voxel-thinning

Open resource ↗QiguanShu/skeleton-abstraction-of-point-cloud-by-voxel-thinning · lines:141-214