RealSense Point Cloud Visualizer in Open3D-Python

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

Provide Docker build sequences of Open3D for various environments.

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

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

TDAzureMerger: a Point-Cloud Merger for Azure Kinects.

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

UI for converting various point cloud file formats

Collision Detection between two 3D objects using Open3D and Octrees

Series of tutorials and assignment to learn how to process acquired 3d data

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

open3d-visualise-point-cloud-in-bin-format

Open3Dを用いた簡単なサンプル

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

GUI, modified reconstruction_system from pen3d

Data Generation: Data is a spherical projection of the 3-D meshes.

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.

Desenvolvimento da documentação/passos necessários para o mapeamento do ambiente. (Fins acadêmicos). Alguns experimentos foram feitos com a Intel realsense r200, outros foram explorando as operações disponíveis no open3D, etc.