The research project based on Semantic KITTTI dataset, 3d Point Cloud Segmentation , Obstacle Detection

3D Point Cloud Visualization - Python - Youtube Tutorial

A QT-based visualization software which can be used to display 3D point clouds from .out and .ply files, which are the outputs of bundler_sfm.

In this project we detect, segment and track the obstacles of an ego car and its custom implementation of KDTree, obstacle detection, segmentation, clustering and tracking algorithm in C++ and compare it to the inbuilt algorithm functions of PCL library on a LiDAR's point cloud data.

Final project titled "Point Cloud Segmentation and Object Tracking using RGB-D Data" for the Machine Vision (EE 576) course.

A research-purposed, GUI-powered, Python-based framework that allows easy development of dynamic point-cloud (and accompanying image) data processing pipelines.

TDAzureMerger: a Point-Cloud Merger for Azure Kinects.

roshell - An interactive shell for robotics applications

Sensor Fusion Nanodegree | Lidar Obstacle Detection in Autonomous Vehicles

Multiview-Structure-From-Motion is an open-source implementation of a complete Structure-from-Motion (SfM) pipeline designed to reconstruct 3D scenes from multiple 2D images. Leveraging advanced computer vision techniques, this project aims to provide a modular and extensible framework.

Tutorial to demonstrate Point Cloud visualization

A research-purposed, GUI-powered, Python-based framework that allows easy development of dynamic point-cloud (and accompanying image) data processing pipelines.

This is a C++ Uni Bonn course project for SoSe 25, which demonstrates the creation of a 3D occupancy grid map from a series of LiDAR scans taken from the 3D LiDAR sensor - Hesai XT-32, mounted on a ClearPath Husky robotic platform. It leverages modern C++17 features, the Eigen library for linear algebra ops and the Open3D library for visualisation