There are 1 repository under pointcloudprocessing topic.
Blender Python PLY importer for point clouds and nonstandard models.
Source code for: Flex-Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds), accepted at ACCV 2018
A fast and simple method for multi-planes detection from point cloud
A script toolkit for SLAM research, including but not limited to various plotting functions, ROS bag processing, and more.
Configurable point cloud registration pipeline.
This is a software for finely removing non-ground points from point clouds.
A unified library for fitting primitives from 3D point cloud data with both C++&Python API.
MandelBrot Fractal Explorer
ROS package for stereo matching and point cloud projection using AANet (Adaptive Aggregation Network for Efficient Stereo Matching, CVPR 2020)
Parallel LiDAR Point Cloud Preprocessing for Autonomous Driving Applications
Implementing a PointNet based architecture for classification and segmentation with point clouds. Q1 and Q2 focus on implementing, training and testing models. Q3 asks you to quantitatively analyze model robustness.
[GMP2024 & CAGD] PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis
Minimal API for obtaining PCL pointcloud using Intel realsense camera.
Lidar project for obstacle detection using PointCloud library.
Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation) with added ROS integration
Transforming 2D images into 3D semantically segmented scenes using innovative CNN architecture and COLMAP reconstruction.
A repository for a set of perception and robotic vision modules, developed by students in Vortex NTNU for use in the AUV and ASV software stacks.
This is the implementation for the reconstruction of 3D scans. These uses multiple algorithms to scale and reconstruct the point cloud in order to obtain valid results
The "Knowledge-based object Detection in Image and Point cloud" (KnowDIP) project aims at the conception of a framework for automatic object detection in unstructured and heterogeneous data. This framework uses a representation of human knowledge in order to improve the flexibility, accuracy, and efficiency of data processing.
3ِD Change Detection In Point Cloud
Command-line interface tool designed for photogrammetry tasks using Meshroom's AliceVision and CloudCompare
Research notebooks on CV automation techniques
A useful tool to cut a set of point cloud into two parts with a designed IoU (overlapping)
Package that can be used to merge multiple sensor_msgs/PointCloud2
A comprehensive pipeline for 3D room segmentation using point cloud data, integrating preprocessing, clustering, plane fitting and semantic segmentation with PointNet/PointNet++ on datasets like S3DIS and KITTI.
Example code to read uncompressed LAS and compressed LAZ files easily using LASlib
Bachelor's thesis project with the aim of creating a tool that can offer the possibility of evaluate the accuracy of classifications identified in high-density point clouds
A curated list of awesome Point Cloud Processing algorithms
Neste Jupyter Notebook ensino como manipular nuvens de pontos 3D com diversas bibliotecas do python. Diversos exemplos de visualização, pré-processamento, registro e alimentação de uma rede neural (MLP) com nuvens de pontos 3D são comentados e testados.
Here you can find some commonly used algorithms in 3D image processing (3D Bildverarbeitung).
Bei der Vermessung eines physischen Raumes ist das Ergebnis eine Punktwolke. Diese Punktwolke beschreibt dann ausgewählte Punkte im Raum, zum Beispiel auf den Wänden und der Decke. Wenn diese Punkte in zwei seperaten Messungen gemessen werden, vielleicht sogar von unterschiedlichen Geräten, soll hinterher herausgefunden werden wie genau diese Punktwolken übereinstimmen. Dafür gibt es zwei grundsätzlich verschiedene Methoden. Diese sollen hier verglichen werden.