Education, research and development using the Simultaneous Localization and Mapping (SLAM) method.
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Updated
Mar 24, 2024 - Python
Education, research and development using the Simultaneous Localization and Mapping (SLAM) method.
Exploring LiDAR dataset (mainly LASer data) with Open3D
Open3D: A Python Library for 3D Data Processing
🛰 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.
RGB-D Scene Reconstruction & Segmentation with Neural Network trained on synthetic database
Surface reconstruction from point cloud showcase app.
Udacity Self Driving Car Nanodegree: sensor fusion midterm proj
3D Point Cloud Processing - General Applications Open3D - Python
3 Data Science Challenges: Crop yield prediction, Weld defects detection and point cloud ground segmentation
3D object reconstruction with multi-view RGB-D images.
The project consists of a program that classifies objects and collects their properties, using point cloud processing and neural networks.
Type stubs for Open3D
3D scene mapping system that using PyTorch's MiDaS model to estimate scene point cloud
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.
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.
Data Generation: Data is a spherical projection of the 3-D meshes.
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