English

Advancing Precision in Multi-Point Cloud Fusion Environments

Computer Vision and Pattern Recognition 2025-08-06 v1 Graphics

Abstract

This research focuses on visual industrial inspection by evaluating point clouds and multi-point cloud matching methods. We also introduce a synthetic dataset for quantitative evaluation of registration method and various distance metrics for point cloud comparison. Additionally, we present a novel CloudCompare plugin for merging multiple point clouds and visualizing surface defects, enhancing the accuracy and efficiency of automated inspection systems.

Keywords

Cite

@article{arxiv.2508.03179,
  title  = {Advancing Precision in Multi-Point Cloud Fusion Environments},
  author = {Ulugbek Alibekov and Vanessa Staderini and Philipp Schneider and Doris Antensteiner},
  journal= {arXiv preprint arXiv:2508.03179},
  year   = {2025}
}

Comments

Accpeted for publication in Communications in Computer and Information Science, Springer

R2 v1 2026-07-01T04:34:42.114Z