heisenberg141/Pointcloud-Segmentation
This repository contains sensor fusion between a lidar and camera, semantic segmentation on point clouds and ICP registration of multiple point clouds.
This project helps operations engineers and robotics developers create detailed 3D maps of environments by combining data from cameras and LiDAR sensors. It takes raw camera images and 3D point cloud data, then processes them to produce semantically labeled, colorized point clouds and a unified, registered 3D map of the scene. This is useful for anyone building perception systems for autonomous vehicles or robotics.
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Use this if you need to merge 2D image information with 3D LiDAR scans to understand and map complex environments, especially for autonomous navigation.
Not ideal if you only have a single type of sensor data (e.g., just a camera or just LiDAR) and don't need to combine them for semantic understanding.
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Language
Python
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Last pushed
Jun 03, 2023
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