🌐 Explore 3D computer vision with Open3D and RealSense for point cloud processing, plane detection, and real-time object detection.
A foundational dive into 3D vision, this project served as my hands-on introduction to processing point clouds with Open3D. I focused on core skills like plane detection, segmentation, and understanding 3D transformations from the ground up.
A high-performance implementation of 3D RANSAC (Random Sample Consensus) algorithm using PyTorch and CUDA.
3D reconstruction from stereo images using epipolar geometry.
[CVPR 2024] AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings
Parallel RANSAC for plane detection for multiple point clouds using Python and CUDA
A python tool for fitting primitives 3D shapes in point clouds using RANSAC algorithm
Semester project for my 3D Computer Geometry & Vision course.
A 3D plane detection approach using PointNet
A python node to detect planes from depth image by using RANSAC algorithm. Input/Output from/to ROS topics.
Put objects on a plane. Use depth camera to find them and add label (for training Yolo).
Add a description, image, and links to the plane-detection topic page so that developers can more easily learn about it.
To associate your repository with the plane-detection topic, visit your repo's landing page and select "manage topics."