Advancing Precision in Multi-Point Cloud Fusion Environments
By: Ulugbek Alibekov , Vanessa Staderini , Philipp Schneider and more
Potential Business Impact:
Finds tiny flaws on factory parts faster.
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.
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