Octree/Quadtree/N-dimensional linear tree
LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".
Header-only N-dimensional BVH library
Semi-automatic YOLO dataset preparation. Use a pre-trained object detection model to annotate your dataset, then review each image and 'accept' or 'refuse'. Can also edit/mark bounding boxes by hand. Store project data in a single .csv file.
This project is a comprehensive tool for detecting intersections between various geometric shapes, including lines, circles, and polygons. It demonstrates fundamental and advanced concepts of computational geometry and intersection detection algorithms, focusing on: Line-Line, Circle-Circle, Line-Circle and Polygon-Polygon Intersections
Bounding Volumes (BV), BV Hierachies and Spatial Partitioning w/ OctTrees + BSPTrees for Spatial Data Structures Study
Template class for clipping 2d polygons to bounding box. Clips also optional attributes such as texcoords and colors.
Add a description, image, and links to the bounding-box topic page so that developers can more easily learn about it.
To associate your repository with the bounding-box topic, visit your repo's landing page and select "manage topics."