Semantic segmentation of airborne lidar data by artificial intelligence

A system for performing a semantic segmentation of a LiDAR point cloud, the system comprising:

• at least one processor;
• at least one memory;
• an acquisition module, configured to receive tiles, each representing a sampled area of the LiDAR point cloud, and a predefined range of optimal column sizes for dividing the tiles;
• an augmentation module, configured to create a plurality of transformed tiles associated with each tile using at least one of:
• rotating the corresponding tile about an axis by a plurality of random angles, and
• dividing the corresponding tile using a specific column size randomly chosen from a predefined range of optimal column sizes;
• a classification module, configured to implement multiple semantic segmentation, the classification module comprising a neural network trained to input one of the plurality of transformed tiles and output a corresponding segmented transformed tile;
• and
• an aggregation module, configured to aggregate a plurality of segmented transformed tiles output by the neural network and create a final semantic segmentation result defining a segmented point cloud including a class for each point of the LiDAR point cloud.

A method for performing a semantic segmentation of a LiDAR point cloud, the method comprising:

• receiving tiles, each representing a sampled area of the LiDAR point cloud, and a predefined range of optimal column sizes for dividing the point cloud tiles;
• creating a plurality of transformed tiles associated with each tile using at least one of:
• rotating the corresponding tile about an axis by a plurality of random angles, and
• dividing the corresponding tile using a specific column size randomly chosen from a predefined range of optimal column sizes
• performing multiple semantic segmentation by a neural network trained to input one of the plurality of transformed tiles and output a corresponding segmented transformed tile;
• and
• aggregating a plurality of segmented transformed tiles output by the neural network to create a final semantic segmentation result defining a segmented point cloud including a class for each point of the LiDAR point cloud.