How to Perform Manual Classification for Deep Learning Using CloudCompare
In this slide, how to perform manual classification for deep learning was introduced. The software used for manual classificaiton was CloudCompare.
This presentation was part of a workshop for CloudCompare users held in Tokyo on April 17, 2024.
Interview of Dr. Daniel by Eugene in YouTube One trend of new functions in CloudCompare is Manual Segmentation Interview with Daniel Girardeau-Montaut, Click 3D Episode 50 https://www.youtube.com/watch?v=sBpi1yHC4xA
below shows the automatic classification using deep learning Point cloud Automatic classification result Annotation data is required for training classification models Manual classification is needed for training data
is also required for evaluating segmentation results • Labeling is also needed to verify the accuracy of studies that count the number of trees Itakura, K., et al. (2021). Estimating tree structural parameters via automatic tree segmentation from LiDAR point cloud data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 555-564.
case of 3D point cloud data to improve the efficiency of patrols of power distribution facilities Classification into Vegetation, Wire and Ground ◼ Ground ◼ Vegetation ◼ Wire Point cloud colored by elevation Auto Classification result
Automatically detect “traces of a path” from point clouds The “traces of a path” leads to places where stones were once extracted for historical structures 高さごとに色分けした図 自動分類した結果 Detected potential traces of a path Input point cloud
manual classification Segment and Merge functions are available for more detailed labeling Data from the Tokyo Metropolitan Government's Digital Twin Realization Project is used