Search Results for "lidar processing"
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Showing 11 open source projects for "lidar processing"
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LAStools
efficient tools for LiDAR processing
LAStools is a collection of efficient, multi-core, scriptable tools for processing LiDAR data. It supports various formats, including LAS, LAZ, Terrasolid BIN, and ESRI Shapefiles, providing a comprehensive suite for LiDAR data management and analysis. -
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FasterLIO
Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry
Faster-LIO is a lightweight, tightly coupled LiDAR-inertial odometry system for pose tracking and point-cloud mapping. It builds on FastLIO2 while replacing key spatial operations with parallel sparse incremental voxels. The design targets high update rates for both solid-state and spinning LiDAR sensors. It fuses LiDAR measurements with inertial data through an iterative Kalman-filter-based estimation pipeline. -
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SLAM in Autonomous Driving Book
SLAM Technology in Autonomous Driving
SLAM in Autonomous Driving Book is the open-source code companion to the book SLAM in Autonomous Driving. It focuses on localization and mapping systems that combine LiDAR, IMU, GNSS, and vehicle motion data. The material begins with geometry, kinematics, Kalman filtering, inertial navigation, preintegration, and graph optimization. It then implements point-cloud processing, nearest-neighbor structures, ICP, NDT, scan matching, occupancy grids, and loop closure. Readers build both loosely coupled and tightly coupled LiDAR-inertial odometry systems. ... -
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SAGA - System for Automated Geoscientific Analyses - is a Geographic Information System (GIS) software with immense capabilities for geodata processing and analysis. SAGA is programmed in the object oriented C++ language and supports the implementation of new functions with a very effective Application Programming Interface (API). Functions are organised as modules in framework independent Module Libraries and can be accessed via SAGA’s Graphical User Interface (GUI) or various scripting...
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MATLAB Deep Learning Model Hub
Discover pretrained models for deep learning in MATLAB
Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score. -
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GLTF/GLB Windows Shell Extension: This shell extension automatically adds thumbnail images to .glb files in Windows File Explorer and provides a right click menu option to generate a 3D preview image for .gltf files. Supports multi-file select and directory processing. Pre-built Windows x64 installer available at https://buymeacoffee.com/nathancrews/e/255640 LAS/LAZ Pointcloud Windows Shell Extension: This "quick viewer" shell extension provides a Windows File Explorer right click menu...
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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. This relatively simple design allows the tracker to achieve very high processing speeds while maintaining competitive tracking accuracy. ... -
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whiteboxgui
An interactive GUI for WhiteboxTools in a Jupyter-based environment
The whiteboxgui Python package is a Jupyter frontend for WhiteboxTools, an advanced geospatial data analysis platform developed by Prof. John Lindsay (webpage; jblindsay) at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image... -
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LiVT
Create a variety of visualisations from high-resolution DTM
The intention behind this Lidar Visualisation Toolbox is to provide an easy-to-use, stand-alone application to create visualisations from high-resolution airborne LIDAR-based digital elevation data. LiVT also includes tools like raster file creation from xyz point clouds. A few mouse clicks and some processing time should be enough to go from an xyz ASCII file to a grey-scale SVF image, an LRM map or a percentage map of cumulative visibility. -
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MCC-LIDAR
Multiscale Curvature Classification for LIDAR Data
MCC-LIDAR is a C++ application for processing LiDAR data in forested environments. It classifies data points as ground or non-ground using the Multiscale Curvature Classification algorithm.
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