Reassembling Broken Objects using Breaking Curves

TL;DR

This paper presents a geometry-based method for reassembling 3D broken objects by segmenting point clouds with breaking curves and evaluating region alignments, demonstrating robustness across various object types.

Contribution

A novel shape-agnostic approach that uses breaking curves for segmenting and aligning 3D point clouds without prior shape information.

Findings

Performs well on real scanned objects

Effective on synthetic broken object benchmarks

Generalizes across diverse object types

Abstract

Reassembling 3D broken objects is a challenging task. A robust solution that generalizes well must deal with diverse patterns associated with different types of broken objects. We propose a method that tackles the pairwise assembly of 3D point clouds, that is agnostic on the type of object, and that relies solely on their geometrical information, without any prior information on the shape of the reconstructed object. The method receives two point clouds as input and segments them into regions using detected closed boundary contours, known as breaking curves. Possible alignment combinations of the regions of each broken object are evaluated and the best one is selected as the final alignment. Experiments were carried out both on available 3D scanned objects and on a recent benchmark for synthetic broken objects. Results show that our solution performs well in reassembling different kinds of broken objects.