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awesome-point-cloud-processing
A curated list of awesome Point Cloud Processing Resources, Libraries, Software
https://github.com/glw/awesome-point-cloud-processing
- Data Structures for Large 3D Point Cloud Processing - Data Structures for Large 3D Point Cloud Processing Tutorial at the 13th International Conference on Intelligent Autonomous Systems
- INF555 Geometric Modeling: Digital Representation and Analysis of Shapes: lecture 7
- Processing lidar and UAV point clouds in GRASS GIS (workshop at FOSS4G Boston 2017)
- Point data manipulation with PDAL
- Pdal Notebooks - Getting Started with PDAL Notebooks, Ground Extraction Using Differential Morphological Profiles.
- Point Cloud Processing - Point cloud classification and modeling using PCL, PDAL, and others
- 500 Billion Points: Organizing Points as infrastructure
- **PCL - Point Cloud Library** - standalone, large scale, open project for 2D/3D image and point cloud processing.
- **3DTK - The 3D Toolkit** - provides algorithms and methods to process 3D point clouds.
- **PDAL - Point Data Abstraction Library** - C++ BSD library for translating and manipulating point cloud data.
- **libLAS** - C/C++ library for reading and writing the very common LAS LiDAR format.
- **Entwine** - data organization library for massive point clouds, designed to conquer datasets of hundreds of billions of points as well as desktop-scale point clouds.
- **PotreeConverter** - another data organisation library, generating data for use in the Potree web viewer.
- **Massive-PotreeConverter** - extends the PotreeConverter to handle massive point cloud data
- **Laspy** - pythonic interface for reading/modifying/creating .LAS LIDAR files matching specification 1.0-1.4.
- **pyfor** - Tools for analyzing point clouds of forest data.
- **laz-perf** - Alternative LAZ implementation for C++ and JavaScript.
- **Paraview** - Open-source, multi-platform data analysis and visualization application.
- **MeshLab** - Open source, portable, and extensible system for the processing and editing of unstructured 3D triangular meshes.
- **CloudCompare** - 3D point cloud and mesh processing software
- **OpenFlipper** - An Open Source Geometry Processing and Rendering Framework.
- **PGpointcloud** - A PostgreSQL extension for storing point cloud (LIDAR) data.
- **Geowave** - GeoWave provides geospatial and temporal indexing on top of Accumulo, HBase, BigTable, Cassandra, and DynamoDB.
- **GRASS** - Geographic Resources Analysis Support System - GIS software suite used for geospatial data management and analysis, image processing, graphics and maps production, spatial modeling, and visualization.
- **fp_denoise** - command-line program for performing feature-preserving de-noising, intented for application with raster digital elevation models (DEMs).
- **lidadrio** - lidario is a simple library for reading and writing LiDAR files stored in LAS format. The library is written using the Go programing language.
- **WhiteboxTools** - WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations... LiDAR data processing. LiDAR point clouds can be interrogated (LidarInfo, LidarHistogram), segmented, tiled and joined, analyized for outliers, interpolated to rasters (DEMs, intensity images), and ground-points can be classified or filtered.
- **FugroViewer** - FugroViewer is a robust, easy-to-use freeware designed to help users make the most of their geospatial data. We have developed it for use with various types of raster- and vector-based geospatial datasets, including data from photogrammetric, lidar, and IFSAR sources. FugroViewer supports the latest open file format for lidar data storage and delivery - American Society for Photogrammetry and Remote Sensing (ASPRS) latest LAS 1.4.
- **LOPoCS** - point cloud server written in Python
- **Greyhound** - a server designed to deliver points from Entwine octrees
- **Potree** - web-based octree viewer written in Javascript.
- **Plasio** - Drag-n-drop In-browser LAS/LAZ point cloud viewer.
- Efficient Processing of Large 3D Point Clouds
- Data Structure for Efficient Processing in 3-D - François Lalonde, Nicolas Vandapel and Martial Hebert, Robotics: Science and Systems I, 2005
- An out-of-core octree for massive point cloud processing
Keywords
las
4
lidar
4
gis
4
pointcloud
3
laz
2
python
2
redis
1
kudu
1
java
1
hbase
1
geowave
1
geospatial-data
1
geoserver
1
dynamodb
1
cassandra
1
accumulo
1
forestry
1
forest-inventory
1
point-cloud
1
copc
1
webgl
1
viewer
1
threejs
1
postgis
1
opensource
1
itowns
1
cesiumjs
1
3d
1
remote-sensing
1
hydrology
1
geospatial
1
geoprocessing
1
geomorphometry
1
geomorphology
1
gis-data
1
geospatial-analysis
1
denoising-images
1
spatiotemporal
1
rocksdb
1