Advancing Precision in Multi-Point Cloud Fusion Environments
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 29 references that are in the map. First posted on arXiv 5 Aug 2025.
Builds on
4 of 29 references.
References · 4
- 2018PCN: Point Completion Networkcited by 384
- 2021Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completioncited by 112
- 2019PCRNet: Point Cloud Registration Network using PointNet Encodingcited by 63
- 2023Cross-source Point Cloud Registration: Challenges, Progress and Prospectscited by 9
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Citing papers per year: 2025: 1.
1 paper.