TriplClust: An Algorithm for Curve Detection in 3D Point Clouds
Christoph Dalitz, Jens Wilberg, Lukas Aymans
⚠ This is a preprint. It may change before it is accepted for publication.


In this article, we describe an algorithm for detecting and separating curves in 3D point clouds without making a priori assumptions about their parametric shape. The algorithm is called 'TriplClust' because it is based on the idea of clustering point triplets instead of the original points. We define a distance measure on point triplets and then apply a single-link hierarchical clustering on the triplets. The clustering process can be controlled by several parameters, which are described in detail, and suggestions for reasonable choices for these parameters based on the input data are made. Moreover, we suggest a simple criterion for stopping the single link clustering automatically.