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UI for converting various point cloud file formats
Implementação do algoritmo ICP (Iterative Closest Point) para nuvens de pontos 3D usando Python.
This repository implements 2D localization for a swarm of milli-robots, simulated in a known environment using inter-robot communication and laser range scans of the environment.
Stereo camera depth estimation with opencv and visualization in Open3D on jetson nano with CUDA support
Examples of point cloud processing in python
Generates projections from viewpoints regularly positioned on a sphere around an object.
Intel RealSense camera to capture depth and color frames and converts them into a 3D point cloud using the Open3D library.
TDAzureMerger: a Point-Cloud Merger for Azure Kinects.
3D Point Cloud Processing - General Applications Open3D - Python
Python code to estimate the volume of a truncated-cylindrical object by fitting profiles to ellipses.
This repository contains the code developed for my MSc project titled "Exploring Photogrammetry for High-Fidelity 3D Model Generation: A Power Grid Inspection Study", as well as some of the results. The thesis was written in collaboration with SINTEF, and the degree issued by DTU. The full thesis can be downloaded from the below link.
Iterative Closet Point (ICP) is an algorithm employed to minimize the difference of two point clouds
An easy-to-use and robust library for seamless interaction with OAK cameras and the DepthAI API. It aims to bridge the gap between the DepthAI API and SDK, allowing for built-in integration with OpenCV and Open3D "out-of-the-box."
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