My Sensor Fusion Kalman Filter Final Project Submission
-
Updated
Aug 6, 2022 - C++
My Sensor Fusion Kalman Filter Final Project Submission
TreeScan3D is an innovative project that leverages the power of 3D computer vision and multi-threaded processing for efficient tree detection. Built using C++ and integrated with the Robot Operating System (ROS), this tool excels at accurately identifying trees in complex environments.
Point Cloud Library Tutorial with ROS
Exploring, learning Edge Detection methods, in Computer Vision, for image processing of building scenes. (PCL 1.11.1 , CMake 3.20.3 , GNU Make 4.3 , Ubuntu 21.04)
MoniGarr’s 5 Week Summer Research Project for the Clarkson University Summer 2023 Research and Project Showcase (RAPS) , Honors Program. Winner of Best Undergraduate Poster Presentation in Computer Science.
Final project titled "Point Cloud Segmentation and Object Tracking using RGB-D Data" for the Machine Vision (EE 576) course.
Configurable point cloud registration pipeline.
Sensor Fusion Nanodegree | Lidar Obstacle Detection in Autonomous Vehicles
Tutorial for using Point Cloud Library (PCL) with ROS 2
FLS point cloud registration library.
A tool to subdivide point clouds into a set of smaller sub point clouds with user defined dimensions.
C++ Repo using Point Cloud Library for Lidar, Radar and Camera sensors
Point Cloud 3D Visual Perception Simulation that runs on real LiDAR data
LiDAR obstacle detection using Voxel Grids, RANSAC, Euclidean Clustering with Kd-Tree in C++ using PCL.
Multi Object Tracking Sensor Fusion 3D Interactive Simulation/Game in PCL
GLIDAR: a simple OpenGL LIDAR simulator
Object detector based on Point Cloud Library and Kinnect Camera
Plane Segmentation and Obstacle Clustering in LiDAR generated point clouds
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.
Add a description, image, and links to the point-cloud-library topic page so that developers can more easily learn about it.
To associate your repository with the point-cloud-library topic, visit your repo's landing page and select "manage topics."