Reassembling Broken Objects using Breaking Curves

Ca' Foscari University of Venice, Department of Computer Science (DAIS)
IEEE 27th International Conference on Pattern Recognition - Kolkata - India
CVPR 2023 Workshop on 3D Vision and Robotics (3DVR)

*Indicates Equal Contribution

Video Presentation

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

Slides

BibTeX


@misc{alagrami2023reassembling,
      title={Reassembling Broken Objects using Breaking Curves},
      author={Ali Alagrami and Luca Palmieri and Sinem Aslan and Marcello Pelillo and Sebastiano Vascon},
      year={2023},
      eprint={2306.02782},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
      

Acknowledgment

This work is part of a project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No.964854.

Results on different datasets.
Results on different datasets.
Results on different datasets.