Education, research and development using the Simultaneous Localization and Mapping (SLAM) method.

3D object reconstruction with multi-view RGB-D images.

Import a point cloud file and perform poisson 3D surface reconstruction algorithm, integrated with third-party libraries (e.g. open3d, pymeshlab...)

Provide Docker build sequences of Open3D for various environments.

The project’s main goal is to investigate real-time object detection and tracking of pedestrians or bicyclists using a Velodyne LiDAR Sensor. Various point-cloud-based algorithms are implemented using the Open3d python package. The resulting 3D point cloud can then be processed to detect objects in the surrounding environment.

3D scene mapping system that using PyTorch's MiDaS model to estimate scene point cloud

Course submission material for Lidar point cloud based 3D Detection using Yolo for Udacity Self Driving Nanodegree

Simple 3D-Scanner/PCD generator using Intel Realsense L515 camera and rotation matrices

Python module to query an fetch the 3D-ARD project

TDAzureMerger: a Point-Cloud Merger for Azure Kinects.

Implementación de algoritmos de aprendizaje no supervisado para realizar clustering a los datos del sensor LIDAR del KITTI-dataset

Type stubs for Open3D

RealSense Point Cloud Visualizer in Open3D-Python

🦾 🎭 An OpenCV based python application to add 3D mask to videos using Google mediapipe

Udacity Self Driving Car Nanodegree: sensor fusion midterm proj

🛰 Ce tutoriel contient des exemples pour cartographier en 3D les nuages de points de terrain de l’émulation planétaire canadienne en Python. 🛰 This tutorial script contains samples for 3D mapping the Canadian Planetary Emulation Terrain point clouds in Python.

UI for converting various point cloud file formats

Generates projections from viewpoints regularly positioned on a sphere around an object.

The project consists of a program that classifies objects and collects their properties, using point cloud processing and neural networks.